Patent Publication Number: US-11394761-B1

Title: Execution of user-submitted code on a stream of data

Description:
RELATED APPLICATIONS 
     This application is being filed concurrently with the following U.S. Applications, each of which is incorporated herein by reference in its entirety: 
     
       
         
           
               
               
               
             
               
                   
               
               
                 U.S. application 
                   
                   
               
               
                 Ser. No. 
                 Title  
                 Filing Date 
               
               
                   
               
             
            
               
                 16,586,619 
                 EXECUTION OF OWNER- 
                 Sep. 27, 2019 
               
               
                   
                 SPECIFIED CODE DURING  
                   
               
               
                   
                 INPUT/OUTPUT PATH TO  
                   
               
               
                   
                 OBJECT STORAGE SERVICE  
                   
               
               
                 16,586,704 
                 INSERTING OWNER-SPECIFIED  
                 Sep. 27, 2019 
               
               
                   
                 DATA PROCESSING PIPELINES  
                   
               
               
                   
                 INTO INPUT/OUTPUT PATH OF  
                   
               
               
                   
                 OBJECT STORAGE SERVICE  
                   
               
               
                 16,586,673 
                 INSERTING EXECUTIONS OF  
                 Sep. 27, 2019 
               
               
                   
                 OWNER-SPECIFIED CODE INTO  
                   
               
               
                   
                 INPUT/OUTPUT PATH OF  
                   
               
               
                   
                 OBJECT STORAGE SERVICE  
                   
               
               
                 16,586,580 
                 ON-DEMAND EXECUTION OF  
                 Sep. 27, 2019 
               
               
                   
                 OBJECT COMBINATION CODE  
                   
               
               
                   
                 IN OUTPUT PATH OF OBJECT  
                   
               
               
                   
                 STORAGE SERVICE  
                   
               
               
                 16,586,562 
                 ON-DEMAND EXECUTION OF  
                 Sep. 27, 2019 
               
               
                   
                 OBJECT TRANSFORMATION  
                   
               
               
                   
                 CODE IN OUTPUT PATH OF 
                   
               
               
                   
                 OBJECT STORAGE SERVICE  
                   
               
               
                 16,586,539 
                 ON-DEMAND EXECUTION OF  
                 Sep. 27, 2019 
               
               
                   
                 OBJECT FILTER CODE  
                   
               
               
                   
                 IN OUTPUT PATH OF OBJECT  
                   
               
               
                   
                 STORAGE SERVICE  
                   
               
               
                 16,586,825 
                 ON-DEMAND CODE  
                 Sep. 27, 2019 
               
               
                   
                 EXECUTION IN INPUT PATH 
                   
               
               
                   
                 DATA UPLOADED TO  
                   
               
               
                   
                 STORAGE SERVICE IN  
                   
               
               
                   
                 MULTIPLE DATA PORTIONS  
                   
               
               
                 16,586,816 
                 ON-DEMAND CODE  
                 Sep. 27, 2019 
               
               
                   
                 OBFUSCATION OF DATA IN  
                   
               
               
                   
                 INPUT PATH OF OBJECT  
                   
               
               
                   
                 STORAGE SERVICE  
                   
               
               
                 16,586,818 
                 ON-DEMAND INDEXING OF  
                 Sep. 27, 2019 
               
               
                   
                 DATA IN INPUT PATH OF  
                   
               
               
                   
                 OBJECT STORAGE SERVICE  
                   
               
               
                 16,586,647 
                 DATA ACCESS CONTROL  
                 Sep. 27, 2019 
               
               
                   
                 SYSTEM FOR OBJECT  
                   
               
               
                   
                 STORAGE SERVICE BASED ON  
                   
               
               
                   
                 OWNER-DEFINED CODE  
                   
               
               
                 16,586,659 
                 USER-SPECIFIC DATA  
                 Sep. 27, 2019 
               
               
                   
                 MANIPULATION SYSTEM FOR  
                   
               
               
                   
                 OBJECT STORAGE SERVICE  
                   
               
               
                   
                 BASED ON USER-SUBMITTED  
                   
               
               
                   
                 CODE  
                   
               
               
                 16,586,686 
                 CODE EXECUTION  
                 Sep. 27, 2019 
               
               
                   
                 ENVIRONMENT  
                   
               
               
                   
                 CUSTOMIZATION SYSTEM  
                   
               
               
                   
                 FOR OBJECT STORAGE  
                   
               
               
                   
                 SERVICE  
                   
               
               
                 16,586,694 
                 SEQUENTIAL EXECUTION OF  
                 Sep. 27, 2019 
               
               
                   
                 USER-SUBMITTED CODE AND  
                   
               
               
                   
                 NATIVE FUNCTIONS 
               
               
                   
               
            
           
         
       
     
     BACKGROUND 
     Computing devices can utilize communication networks to exchange data. Companies and organizations operate computer networks that interconnect a number of computing devices to support operations or to provide services to third parties. The computing devices can be located in a single geographic location or located in multiple, distinct geographic locations (e.g., interconnected via private or public communication networks). Specifically, data centers or data processing centers, herein generally referred to as a “data center,” may include a number of interconnected computing systems to provide computing resources to users of the data center. The data centers may be private data centers operated on behalf of an organization or public data centers operated on behalf, or for the benefit of, the general public. 
     To facilitate increased utilization of data center resources, virtualization technologies allow a single physical computing device to host one or more instances of virtual machines that appear and operate as independent computing devices to users of a data center. With virtualization, the single physical computing device can create, maintain, delete, or otherwise manage virtual machines in a dynamic manner. In turn, users can request computer resources from a data center, including single computing devices or a configuration of networked computing devices, and be provided with varying numbers of virtual machine resources. 
     In addition to computational resources, data centers provide a number of other beneficial services to client devices. For example, data centers may provide data storage services configured to store data submitted by client devices, and enable retrieval of that data over a network. A variety of types of data storage services can be provided, often varying according to their input/output (I/O) mechanisms. For example, database services may allow I/O based on a database query language, such as the Structured Query Language (SQL). Block storage services may allow I/O based on modification to one or more defined-length blocks, in a manner similar to how an operating system interacts with local storage, and may thus facilitate virtualized disk drives usable, for example, to store an operating system of a virtual machine. Object storage services may allow I/O at the level of individual objects or resources, such as individual files, which may vary in content and length. For example, an object storage service may provide an interface compliant with the Representational State Transfer (REST) architectural style, such as by allowing I/O based on calls designating input data and a hypertext transport protocol request method (e.g., GET, PUT, POST, DELETE, etc.) to be applied to that data. By transmitting a call designating input data and a request method, a client can thus retrieve the data from an object storage service, write the data to the object storage service as a new object, modify an existing object, etc. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         FIG. 1  is a block diagram depicting an illustrative environment in which an object storage service can operate in conjunction with an on-demand code execution system to implement functions in connection with input/output (I/O) requests to the object storage service; 
         FIG. 2  depicts a general architecture of a computing device providing a frontend of the object storage service of  FIG. 1 ; 
         FIG. 3  is a flow diagram depicting illustrative interactions for enabling a client device to modify an I/O path for the object storage service by insertion of a function implemented by execution of a task on the on-demand code execution system; 
         FIG. 4  is an illustrative visualization of a pipeline of functions to be applied to an I/O path for the object storage service of  FIG. 1 ; 
         FIGS. 5A-5B  show a flow diagram depicting illustrative interactions for handling a request to store input data as an object on the object storage service of  FIG. 1 , including execution of an owner-specified task to the input data and storage of output of the task as the object; 
         FIGS. 6A-6B  show a flow diagram depicting illustrative interactions for handling a request to retrieve data of an object on the object storage service of  FIG. 1 , including execution of an owner-specified task to the object and transmission of an output of the task to a requesting device as the object; 
         FIG. 7  is a flow chart depicting an illustrative routine for implementing owner-defined functions in connection with an I/O request obtained at the object storage service of  FIG. 1  over an I/O path; 
         FIG. 8  is a flow chart depicting an illustrative routine for executing a task on the on-demand code execution system of  FIG. 1  to enable data manipulations during implementation of an owner-defined function; 
         FIG. 9  is another block diagram of the illustrative operating environment of  FIG. 1  in which a staging environment operates to fetch objects for execution by the task code and manage output data produced by execution of the task code; 
         FIG. 10  is a block diagram of the illustrative operating environment of  FIG. 1  illustrating the operations performed by the components of the operating environment to fetch an entire object and produce a single instance of output data as a result, according to one embodiment; 
         FIGS. 11A-11B  are block diagrams of the illustrative operating environment of  FIG. 1  illustrating the operations performed by the components of the operating environment to fetch a stream of input data and to produce a stream of output data, according to one embodiment; 
         FIGS. 12A-12B  are block diagrams of the illustrative operating environment of  FIG. 1  illustrating the operations performed by the components of the operating environment to fetch input data on-demand to produce a single instance of output data, according to one embodiment; 
         FIG. 13  is a flow chart depicting an illustrative routine for processing a streamed object on the on-demand code execution system of  FIG. 1 ; and 
         FIG. 14  is a flow chart depicting an illustrative routine for processing an object fetched on-demand on the on-demand code execution system of  FIG. 1 . 
     
    
    
     DETAILED DESCRIPTION 
     Generally described, aspects of the present disclosure relate to handling requests to read or write to data objects on an object storage system. More specifically, aspects of the present disclosure relate to modification of an input/output (I/O) path for an object storage service, such that one or more data manipulations can be inserted into the I/O path to modify the data to which a called request method is applied, without requiring a calling client device to specify such data manipulations. In one embodiment, data manipulations occur through execution of user-submitted code, which may be provided for example by an owner of a collection of data objects on an object storage system in order to control interactions with that data object. For example, in cases where an owner of an object collection wishes to ensure that end users do not submit objects to the collection including any personally identifying information (to ensure end user&#39;s privacy), the owner may submit code executable to strip such information from a data input. The owner may further specify that such code should be executed during each write of a data object to the collection. Accordingly, when an end user attempts to write input data to the collection as a data object (e.g., via an HTTP PUT method), the code may be first executed against the input data, and resulting output data may be written to the collection as the data object. Notably, this may result in the operation requested by the end user—such as a write operation—being applied not to the end user&#39;s input data, but instead to the data output by the data manipulation (e.g., owner-submitted) code. In this way, owners of data collections control I/O to those collections without relying on end users to comply with owner requirements. Indeed, end users (or any other client device) may be unaware that modifications to I/O are occurring. As such, embodiments of the present disclosure enable modification of I/O to an object storage service without modification of an interface to the service, ensuring inter-compatibility with other pre-existing software utilizing the service. 
     In some embodiments of the present disclosure, data manipulations may occur on an on-demand code execution system, sometimes referred to as a serverless execution system. Generally described, on-demand code execution systems enable execution of arbitrary user-designated code, without requiring the user to create, maintain, or configure an execution environment (e.g., a physical or virtual machine) in which the code is executed. For example, whereas conventional computing services often require a user to provision a specific device (virtual or physical), install an operating system on the device, configure applications, define network interfaces, and the like, an on-demand code execution system may enable a user to submit code and may provide to the user an application programming interface (API) that, when used, enables the user to request execution of the code. On receiving a call through the API, the on-demand code execution system may generate an execution environment for the code, provision the environment with the code, execute the code, and provide a result. Thus, an on-demand code execution system can remove a need for a user to handle configuration and management of environments for code execution. Example techniques for implementing an on-demand code execution system are disclosed, for example, within U.S. Pat. No. 9,323,556, entitled “PROGRAMMATIC EVENT DETECTION AND MESSAGE GENERATION FOR REQUESTS TO EXECUTE PROGRAM CODE,” and filed Sep. 30, 2014 (the “&#39;556 Patent”), the entirety of which is hereby incorporated by reference. 
     Due to the flexibility of an on-demand code execution system to execute arbitrary code, such a system can be used to create a variety of network services. For example, such a system could be used to create a “micro-service,” a network service that implements a small number of functions (or only one function), and that interacts with other services to provide an application. In the context of on-demand code execution systems, the code executed to create such a service is often referred to as a “function” or a “task,” which can be executed to implement the service. Accordingly, one technique for performing data manipulations within the I/O path of an object storage service may be to create a task on an on-demand code execution system that, when executed, performs the required data manipulation. Illustratively, the task could provide an interface similar or identical to that of the object storage service, and be operable to obtain input data in response to a request method call (e.g., HTTP PUT or GET calls), execute the code of the task against the input data, and perform a call to the object storage service for implementation of the request method on resulting output data. A downside of this technique is a complexity. For example, end users might be required under this scenario to submit I/O requests to the on-demand code execution system, rather than the object storage service, to ensure execution of the task. Should an end user submit a call directly to the object storage service, task execution may not occur, and thus an owner would not be enabled to enforce a desired data manipulation for an object collection. In addition, this technique may require that code of a task be authored to both provide an interface to end users that enables handling of calls to implement request methods on input data, and an interface that enables performance of calls from the task execution to the object storage service. Implementation of these network interfaces may significantly increase the complexity of the required code, thus disincentivizing owners of data collections from using this technique. Moreover, where user-submitted code directly implements network communication, that code may need to be varied according to the request method handled. For example, a first set of code may be required to support GET operations, a second set of code may be required to support PUT operations, etc. Because embodiments of the present disclosure relieve the user-submitted code of the requirement of handling network communications, one set of code may in some cases be enabled to handle multiple request methods. 
     To address the above-noted problems, embodiments of the present disclosure can enable strong integration of serverless task executions with interfaces of an object storage service, such that the service itself is configured to invoke a task execution on receiving an I/O request to a data collection. Moreover, generation of code to perform data manipulations may be simplified by configuring the object storage service to facilitate data input and output from a task execution, without requiring the task execution to itself implement network communications for I/O operations. Specifically, an object storage service and on-demand code execution system can be configured in one embodiment to “stage” input data to a task execution in the form of a handle (e.g., a POSIX-compliant descriptor) to an operating-system-level input/output stream, such that code of a task can manipulate the input data via defined-stream operations (e.g., as if the data existed within a local file system). This stream-level access to input data can be contrasted, for example, with network-level access of input data, which generally requires that code implement network communication to retrieve the input data. The input data staged to the input staging area (e.g., memory or disk) pointed to by the input stream (e.g., file) handle can be an entire object or a portion of an object, and the same task code can manipulate either an entire object or a portion of an object without being modified. For example, the object storage service and on-demand code execution system can write an entire object to the input staging area pointed to by the input file handle in some circumstances, and the code of the task can manipulate the entire object to produce output data. Memory or a disk pointed to by the input file handle may have a finite amount of available storage, however, and therefore a large object (e.g., a multi-terabyte object) may not fit in the memory or disk. Thus, in these circumstances or in any other circumstances in which it is not desired to process an entire object at once (e.g., a time to fetch and/or process an entire object would exceed a threshold time, possibly resulting in a delay noticeable to a user), the object storage service and on-demand code execution system can write a portion of an object to the input staging area pointed to by the input file handle, and the code of the task can manipulate the object portion to produce output data. Once the object portion is read from the input staging area pointed to by the input file handle (e.g., by the task execution) and/or in accordance with a fetch process, the object storage service and on-demand code execution system can write another portion of the object to the input file handle if any portions of the object to be manipulated remain, and the code of the task can manipulate this other portion of the object to produce additional output data. This process can be repeated until some or all portions of an object are manipulated by the code of the task. In this way, the input staging area pointed to by the input file handle serves as a set, known local storage location at which input data is stored, and the task code can perform the same data retrieval and manipulation operations on the input data regardless of whether the input data is an entire object or a portion of an object. 
     Similarly, the object storage service and on-demand code execution system can be configured to provide an output stream handle representing an output stream that points to an output staging area (e.g., memory or disk) to which a task execution may write output. On detecting writes to the output file handle, the object storage service and on-demand code execution system may handle such writes as output data of the task execution, and apply a called request method to the output data. The task execution can write a single piece of output data to the output staging area pointed to by the output file handle or can write a stream of output data to the output staging area pointed to by the output file handle. For example, the task execution can write a single piece of output data to the output staging area pointed to by the output file handle in response to a manipulation of an entire object or a stream of object portions written to the input file handle. As another example, the task execution can produce a stream of output data, where different portions of the output data stream are written to the output staging area pointed to by the output file handle in sequence. The task execution can produce the stream of output data in response to a manipulation of an entire object or a stream of object portions written to the input staging area pointed to by the input file handle. By enabling a task to manipulate data based on input and output streams passed to the task, as opposed to requiring the code to handle data communications over a network, the code of the task can be greatly simplified. 
     Another benefit of enabling a task to manipulate data based on input and output handles is increased security. A general-use on-demand code execution system may operate permissively with respect to network communications from a task execution, enabling any network communication from the execution unless such communication is explicitly denied. This permissive model is reflective of the use of task executions as micro-services, which often require interaction with a variety of other network services. However, this permissive model also decreases security of the function, since potentially malicious network communications can also reach the execution. In contrast to a permissive model, task executions used to perform data manipulations on an object storage system&#39;s I/O path can utilize a restrictive model, whereby only explicitly-allowed network communications can occur from an environment executing a task. Illustratively, because data manipulation can occur via input and output handles, it is envisioned that many or most tasks used to perform data manipulation in embodiments of the present disclosure would require no network communications to occur at all, greatly increasing security of such an execution. Where a task execution does require some network communications, such as to contact an external service to assist with a data manipulation, such communications can be explicitly allowed, or “whitelisted,” thus exposing the execution in only a strictly limited manner. 
     In some embodiments, a data collection owner may require only a single data manipulation to occur with respect to I/O to the collection. Accordingly, the object storage service may detect I/O to the collection, implement the data manipulation (e.g., by executing a serverless task within an environment provisioned with input and output handles), and apply the called request method to the resulting output data. In other embodiments, an owner may request multiple data manipulations occur with respect to an I/O path. For example, to increase portability and reusability, an owner may author multiple serverless tasks, which may be combined in different manners on different I/O paths. Thus, for each path, the owner may define a series of serverless tasks to be executed on I/O to the path. Moreover, in some configurations, an object storage system may natively provide one or more data manipulations. For example, an object storage system may natively accept requests for only portions of an object (e.g., of a defined byte range), or may natively enable execution of queries against data of an object (e.g., SQL queries). In some embodiments, any combination of and any number of various native manipulations and serverless task-based manipulations may be specified for a given I/O path. For example, an owner may specify that, for a particular request to read an object, a given SQL query be executed against the object, the output of which is processed via a first task execution, the output of which is processed via a second task execution, etc. The collection of data manipulations (e.g., native manipulations, serverless task-based manipulations, or a combination thereof) applied to an I/O path is generally referred to herein as a data processing “pipeline” applied to the I/O path. 
     In accordance with aspects of the present disclosure, a particular path modification (e.g., the addition of a pipeline) applied to an I/O path may vary according to attributes of the path, such as a client device from which an I/O request originates or an object or collection of objects within the request. For example, pipelines may be applied to individual objects, such that the pipeline is applied to all I/O requests for the object, or a pipeline may be selectively applied only when certain client devices (or users) access the object. In some instances, an object storage service may provide multiple I/O paths for an object or collection. For example, the same object or collection may be associated with multiple resource identifiers on the object storage service, such that the object or collection can be accessed through the multiple identifiers (e.g., uniform resource identifiers, or URIs), which illustratively correspond to different network-accessible endpoints. In one embodiment, different pipelines may be applied to each I/O path for a given object. For example, a first I/O path may be associated with unprivileged access to a data set, and thus be subject to data manipulations that remove confidential information from the data set prior during retrieval. A second I/O path may be associated with privileged access, and thus not be subject to those data manipulations. An output of metadata associated with a serverless task-based manipulation, for example, may determine which I/O path is selected for a given object. In some instances, pipelines may be selectively applied based on other criteria. For example, whether a pipeline is applied may be based on time of day, a number or rate of accesses to an object or collection, a role of a user operating a client device attempting to access an object (e.g., work responsibilities of the user, such as tasks assigned to the user and/or tasks not assigned to the user), etc. 
     As will be appreciated by one of skill in the art in light of the present disclosure, the embodiments disclosed herein improve the ability of computing systems, such as object storage systems, to provide and enforce data manipulation functions against data objects. Whereas prior techniques generally depend on external enforcement of data manipulation functions (e.g., requesting that users strip personal information before uploading it), embodiments of the present disclosure enable direct insertion of data manipulation into an I/O path for the object storage system. Thus, administrators can allow users to use third party applications that may have a wide mix of different software and capabilities to open and/or manipulate data files without having to verify that such third party applications filter data appropriately or otherwise prevent users from accessing sensitive information. Moreover, embodiments of the present disclosure provide a secure mechanism for implementing data manipulations, by providing for serverless execution of manipulation functions within an isolated execution environment. Embodiments of the present disclosure further improve operation of serverless functions, by enabling such functions to operate on the basis of local stream (e.g., “file”) handles, rather than requiring that functions act as network-accessible services. The presently disclosed embodiments therefore address technical problems inherent within computing systems, such as the difficulty of enforcing data manipulations at storage systems and the complexity of creating external services to enforce such data manipulations. These technical problems are addressed by the various technical solutions described herein, including the insertion of data processing pipelines into an I/O path for an object or object collection, potentially without knowledge of a requesting user, the use of serverless functions and/or native functions to perform aspects of such pipelines, and the use of local stream handles to enable simplified creation of serverless functions. Thus, the present disclosure represents an improvement on existing data processing systems and computing systems in general. 
     The general execution of tasks on the on-demand code execution system will now be discussed. As described in detail herein, the on-demand code execution system may provide a network-accessible service enabling users to submit or designate computer-executable source code to be executed by virtual machine instances on the on-demand code execution system. Each set of code on the on-demand code execution system may define a “task,” and implement specific functionality corresponding to that task when executed on a virtual machine instance of the on-demand code execution system. Individual implementations of the task on the on-demand code execution system may be referred to as an “execution” of the task (or a “task execution”). In some cases, the on-demand code execution system may enable users to directly trigger execution of a task based on a variety of potential events, such as transmission of an application programming interface (“API”) call to the on-demand code execution system, or transmission of a specially formatted hypertext transport protocol (“HTTP”) packet to the on-demand code execution system. In accordance with embodiments of the present disclosure, the on-demand code execution system may further interact with an object storage system, in order to execute tasks during application of a data manipulation pipeline to an I/O path. The on-demand code execution system can therefore execute any specified executable code “on-demand,” without requiring configuration or maintenance of the underlying hardware or infrastructure on which the code is executed. Further, the on-demand code execution system may be configured to execute tasks in a rapid manner (e.g., in under 100 milliseconds [ms]), thus enabling execution of tasks in “real-time” (e.g., with little or no perceptible delay to an end user). To enable this rapid execution, the on-demand code execution system can include one or more virtual machine instances that are “pre-warmed” or pre-initialized (e.g., booted into an operating system and executing a complete or substantially complete runtime environment) and configured to enable execution of user-defined code, such that the code may be rapidly executed in response to a request to execute the code, without delay caused by initializing the virtual machine instance. Thus, when an execution of a task is triggered, the code corresponding to that task can be executed within a pre-initialized virtual machine in a very short amount of time. 
     Specifically, to execute tasks, the on-demand code execution system described herein may maintain a pool of executing virtual machine instances that are ready for use as soon as a request to execute a task is received. Due to the pre-initialized nature of these virtual machines, delay (sometimes referred to as latency) associated with executing the task code (e.g., instance and language runtime startup time) can be significantly reduced, often to sub-100 millisecond levels. Illustratively, the on-demand code execution system may maintain a pool of virtual machine instances on one or more physical computing devices, where each virtual machine instance has one or more software components (e.g., operating systems, language runtimes, libraries, etc.) loaded thereon. When the on-demand code execution system receives a request to execute program code (a “task”), the on-demand code execution system may select a virtual machine instance for executing the program code of the user based on the one or more computing constraints related to the task (e.g., a required operating system or runtime) and cause the task to be executed on the selected virtual machine instance. The tasks can be executed in isolated containers that are created on the virtual machine instances, or may be executed within a virtual machine instance isolated from other virtual machine instances acting as environments for other tasks. Since the virtual machine instances in the pool have already been booted and loaded with particular operating systems and language runtimes by the time the requests are received, the delay associated with finding compute capacity that can handle the requests (e.g., by executing the user code in one or more containers created on the virtual machine instances) can be significantly reduced. 
     As used herein, the term “virtual machine instance” is intended to refer to an execution of software or other executable code that emulates hardware to provide an environment or platform on which software may execute (an example “execution environment”). Virtual machine instances are generally executed by hardware devices, which may differ from the physical hardware emulated by the virtual machine instance. For example, a virtual machine may emulate a first type of processor and memory while being executed on a second type of processor and memory. Thus, virtual machines can be utilized to execute software intended for a first execution environment (e.g., a first operating system) on a physical device that is executing a second execution environment (e.g., a second operating system). In some instances, hardware emulated by a virtual machine instance may be the same or similar to hardware of an underlying device. For example, a device with a first type of processor may implement a plurality of virtual machine instances, each emulating an instance of that first type of processor. Thus, virtual machine instances can be used to divide a device into a number of logical sub-devices (each referred to as a “virtual machine instance”). While virtual machine instances can generally provide a level of abstraction away from the hardware of an underlying physical device, this abstraction is not required. For example, assume a device implements a plurality of virtual machine instances, each of which emulate hardware identical to that provided by the device. Under such a scenario, each virtual machine instance may allow a software application to execute code on the underlying hardware without translation, while maintaining a logical separation between software applications running on other virtual machine instances. This process, which is generally referred to as “native execution,” may be utilized to increase the speed or performance of virtual machine instances. Other techniques that allow direct utilization of underlying hardware, such as hardware pass-through techniques, may be used, as well. 
     While a virtual machine executing an operating system is described herein as one example of an execution environment, other execution environments are also possible. For example, tasks or other processes may be executed within a software “container,” which provides a runtime environment without itself providing virtualization of hardware. Containers may be implemented within virtual machines to provide additional security, or may be run outside of a virtual machine instance. 
     The foregoing aspects and many of the attendant advantages of this disclosure will become more readily appreciated as the same become better understood by reference to the following description, when taken in conjunction with the accompanying drawings. 
       FIG. 1  is a block diagram of an illustrative operating environment  100  in which a service provider system  110  operates to enable client devices  102  to perform I/O operations on objects stored within an object storage service  160  and to apply path modifications to such I/O operations, which modifications may include execution of user-defined code on an on-demand code execution system  120 . 
     By way of illustration, various example client devices  102  are shown in communication with the service provider system  110 , including a desktop computer, laptop, and a mobile phone. In general, the client devices  102  can be any computing device such as a desktop, laptop or tablet computer, personal computer, wearable computer, server, personal digital assistant (PDA), hybrid PDA/mobile phone, mobile phone, electronic book reader, set-top box, voice command device, camera, digital media player, and the like. 
     Generally described, the object storage service  160  can operate to enable clients to read, write, modify, and delete data objects, each of which represents a set of data associated with an identifier (an “object identifier” or “resource identifier”) that can be interacted with as an individual resource. For example, an object may represent a single file submitted by a client device  102  (though the object storage service  160  may or may not store such an object as a single file). This object-level interaction can be contrasted with other types of storage services, such as block-based storage services providing data manipulation at the level of individual blocks or database storage services providing data manipulation at the level of tables (or parts thereof) or the like. 
     The object storage service  160  illustratively includes one or more frontends  162 , which provide an interface (a command-line interface (CLIs), application programing interface (APIs), or other programmatic interface) through which client devices  102  can interface with the service  160  to configure the service  160  on their behalf and to perform I/O operations on the service  160 . For example, a client device  102  may interact with a frontend  162  to create a collection of data objects on the service  160  (e.g., a “bucket” of objects) and to configure permissions for that collection. Client devices  102  may thereafter create, read, update, or delete objects within the collection based on the interfaces of the frontends  162 . In one embodiment, the frontend  162  provides a REST-compliant HTTP interface supporting a variety of request methods, each of which corresponds to a requested I/O operation on the service  160 . By way of non-limiting example, request methods may include:
         a GET operation requesting retrieval of an object stored on the service  160  by reference to an identifier of the object;   a PUT operation requesting storage of an object to be stored on the service  160 , including an identifier of the object and input data to be stored as the object;   a DELETE operation requesting deletion of an object stored on the service  160  by reference to an identifier of the object; and   a LIST operation requesting listing of objects within an object collection stored on the service  160  by reference to an identifier of the collection.
 
A variety of other operations may also be supported. For example, the service  160  may provide a POST operation similar to a PUT operation but associated with a different upload mechanism (e.g., a browser-based HTML upload), or a HEAD operation enabling retrieval of metadata for an object without retrieving the object itself. In some embodiments, the service  160  may enable operations that combine one or more of the above operations, or combining an operation with a native data manipulation. For example, the service  160  may provide a COPY operation enabling copying of an object stored on the service  160  to another object, which operation combines a GET operation with a PUT operation. As another example, the service  160  may provide a SELECT operation enabling specification of an SQL query to be applied to an object prior to returning the contents of that object, which combines an application of an SQL query to a data object (a native data manipulation) with a GET operation. As yet another example, the service  160  may provide a “byte range” GET, which enables a GET operation on only a portion of a data object. In some instances, the operation requested by a client device  102  on the service  160  may be transmitted to the service via an HTTP request, which itself may include an HTTP method. In some cases, such as in the case of a GET operation, the HTTP method specified within the request may match the operation requested at the service  160 . However, in other cases, the HTTP method of a request may not match the operation requested at the service  160 . For example, a request may utilize an HTTP POST method to transmit a request to implement a SELECT operation at the service  160 .
       

     During general operation, frontends  162  may be configured to obtain a call to a request method, and apply that request method to input data for the method. For example, a frontend  162  can respond to a request to PUT input data into the service  160  as an object by storing that input data as the object on the service  160 . Objects may be stored, for example, on object data stores  168 , which correspond to any persistent or substantially persistent storage (including hard disk drives (HDDs), solid state drives (SSDs), network accessible storage (NAS), storage area networks (SANs), non-volatile random access memory (NVRAM), or any of a variety of storage devices known in the art). As a further example, the frontend  162  can respond to a request to GET an object from the service  160  by retrieving the object from the stores  168  (the object representing input data to the GET resource request), and returning the object to a requesting client device  102 . 
     In some cases, calls to a request method may invoke one or more native data manipulations provided by the service  160 . For example, a SELECT operation may provide an SQL-formatted query to be applied to an object (also identified within the request), or a GET operation may provide a specific range of bytes of an object to be returned. The service  160  illustratively includes an object manipulation engine  170  configured to perform native data manipulations, which illustratively corresponds to a device configured with software executable to implement native data manipulations on the service  160  (e.g., by stripping non-selected bytes from an object for a byte-range GET, by applying an SQL query to an object and returning results of the query, etc.). 
     In accordance with embodiments of the present disclosure, the service  160  can further be configured to enable modification of an I/O path for a given object or collection of objects, such that a called request method is applied to an output of a data manipulation function, rather than the resource identified within the call. For example, the service  160  may enable a client device  102  to specify that GET operations for a given object should be subject to execution of a user-defined task on the on-demand code execution system  120 , such that the data returned in response to the operation is the output of a task execution rather than the requested object. Similarly, the service  160  may enable a client device  102  to specify that PUT operations to store a given object should be subject to execution of a user-defined task on the on-demand code execution system  120 , such that the data stored in response to the operation is the output of a task execution rather than the data provided for storage by a client device  102 . As will be discussed in more detail below, path modifications may include specification of a pipeline of data manipulations, including native data manipulations, task-based manipulations, or combinations thereof. Illustratively, a client device  102  may specify a pipeline or other data manipulation for an object or object collection through the frontend  162 , which may store a record of the pipeline or manipulation in the I/O path modification data store  164 , which store  164 , like the object data stores  168 , can represent any persistent or substantially persistent storage. While shown as distinct in  FIG. 1 , in some instances the data stores  164  and  168  may represent a single collection of data stores. For example, data modifications to objects or collections may themselves be stored as objects on the service  160 . 
     To enable data manipulation via execution of user-defined code, the system further includes an on-demand code execution system  120 . In one embodiment, the system  120  is solely usable by the object storage service  160  in connection with data manipulations of an I/O path. In another embodiment, the system  120  is additionally accessible by client devices  102  to directly implement serverless task executions. For example, the on-demand code execution system  120  may provide the service  160  (and potentially client devices  102 ) with one or more user interfaces, command-line interfaces (CLIs), application programing interfaces (APIs), or other programmatic interfaces for generating and uploading user-executable code (e.g., including metadata identifying dependency code objects for the uploaded code), invoking the user-provided code (e.g., submitting a request to execute the user codes on the on-demand code execution system  120 ), scheduling event-based jobs or timed jobs, tracking the user-provided code, or viewing other logging or monitoring information related to their requests or user codes. Although one or more embodiments may be described herein as using a user interface, it should be appreciated that such embodiments may, additionally or alternatively, use any CLIs, APIs, or other programmatic interfaces. 
     The client devices  102 , object storage service  160 , and on-demand code execution system  120  may communicate via a network  104 , which may include any wired network, wireless network, or combination thereof. For example, the network  104  may be a personal area network, local area network, wide area network, over-the-air broadcast network (e.g., for radio or television), cable network, satellite network, cellular telephone network, or combination thereof. As a further example, the network  104  may be a publicly accessible network of linked networks, possibly operated by various distinct parties, such as the Internet. In some embodiments, the network  104  may be a private or semi-private network, such as a corporate or university intranet. The network  104  may include one or more wireless networks, such as a Global System for Mobile Communications (GSM) network, a Code Division Multiple Access (CDMA) network, a Long Term Evolution (LTE) network, or any other type of wireless network. The network  104  can use protocols and components for communicating via the Internet or any of the other aforementioned types of networks. For example, the protocols used by the network  104  may include Hypertext Transfer Protocol (HTTP), HTTP Secure (HTTPS), Message Queue Telemetry Transport (MQTT), Constrained Application Protocol (CoAP), and the like. Protocols and components for communicating via the Internet or any of the other aforementioned types of communication networks are well known to those skilled in the art and, thus, are not described in more detail herein. 
     To enable interaction with the on-demand code execution system  120 , the system  120  includes one or more frontends  130 , which enable interaction with the on-demand code execution system  120 . In an illustrative embodiment, the frontends  130  serve as a “front door” to the other services provided by the on-demand code execution system  120 , enabling users (via client devices  102 ) or the service  160  to provide, request execution of, and view results of computer executable code. The frontends  130  include a variety of components to enable interaction between the on-demand code execution system  120  and other computing devices. For example, each frontend  130  may include a request interface providing client devices  102  and the service  160  with the ability to upload or otherwise communication user-specified code to the on-demand code execution system  120  and to thereafter request execution of that code. In one embodiment, the request interface communicates with external computing devices (e.g., client devices  102 , frontend  162 , etc.) via a graphical user interface (GUI), CLI, or API. The frontends  130  process the requests and make sure that the requests are properly authorized. For example, the frontends  130  may determine whether the user associated with the request is authorized to access the user code specified in the request. 
     References to user code as used herein may refer to any program code (e.g., a program, routine, subroutine, thread, etc.) written in a specific program language. In the present disclosure, the terms “code,” “user code,” and “program code,” may be used interchangeably. Such user code may be executed to achieve a specific function, for example, in connection with a particular data transformation developed by the user. As noted above, individual collections of user code (e.g., to achieve a specific function) are referred to herein as “tasks,” while specific executions of that code (including, e.g., compiling code, interpreting code, or otherwise making the code executable) are referred to as “task executions” or simply “executions.” Tasks may be written, by way of non-limiting example, in JavaScript (e.g., node.js), Java, Python, or Ruby (or another programming language). 
     To manage requests for code execution, the frontend  130  can include an execution queue, which can maintain a record of requested task executions. Illustratively, the number of simultaneous task executions by the on-demand code execution system  120  is limited, and as such, new task executions initiated at the on-demand code execution system  120  (e.g., via an API call, via a call from an executed or executing task, etc.) may be placed on the execution queue and processed, e.g., in a first-in-first-out order. In some embodiments, the on-demand code execution system  120  may include multiple execution queues, such as individual execution queues for each user account. For example, users of the service provider system  110  may desire to limit the rate of task executions on the on-demand code execution system  120  (e.g., for cost reasons). Thus, the on-demand code execution system  120  may utilize an account-specific execution queue to throttle the rate of simultaneous task executions by a specific user account. In some instances, the on-demand code execution system  120  may prioritize task executions, such that task executions of specific accounts or of specified priorities bypass or are prioritized within the execution queue. In other instances, the on-demand code execution system  120  may execute tasks immediately or substantially immediately after receiving a call for that task, and thus, the execution queue may be omitted. 
     The frontend  130  can further include an output interface configured to output information regarding the execution of tasks on the on-demand code execution system  120 . Illustratively, the output interface may transmit data regarding task executions (e.g., results of a task, errors related to the task execution, or details of the task execution, such as total time required to complete the execution, total data processed via the execution, etc.) to the client devices  102  or the object storage service  160 . 
     In some embodiments, the on-demand code execution system  120  may include multiple frontends  130 . In such embodiments, a load balancer may be provided to distribute the incoming calls to the multiple frontends  130 , for example, in a round-robin fashion. In some embodiments, the manner in which the load balancer distributes incoming calls to the multiple frontends  130  may be based on the location or state of other components of the on-demand code execution system  120 . For example, a load balancer may distribute calls to a geographically nearby frontend  130 , or to a frontend with capacity to service the call. In instances where each frontend  130  corresponds to an individual instance of another component of the on-demand code execution system  120 , such as the active pool  148  described below, the load balancer may distribute calls according to the capacities or loads on those other components. Calls may in some instances be distributed between frontends  130  deterministically, such that a given call to execute a task will always (or almost always) be routed to the same frontend  130 . This may, for example, assist in maintaining an accurate execution record for a task, to ensure that the task executes only a desired number of times. For example, calls may be distributed to load balance between frontends  130 . Other distribution techniques, such as anycast routing, will be apparent to those of skill in the art. 
     The on-demand code execution system  120  further includes one or more worker managers  140  that manage the execution environments, such as virtual machine instances  150  (shown as VM instance  150 A and  150 B, generally referred to as a “VM”), used for servicing incoming calls to execute tasks. While the following will be described with reference to virtual machine instances  150  as examples of such environments, embodiments of the present disclosure may utilize other environments, such as software containers. In the example illustrated in  FIG. 1 , each worker manager  140  manages an active pool  148 , which is a group (sometimes referred to as a pool) of virtual machine instances  150  executing on one or more physical host computing devices that are initialized to execute a given task (e.g., by having the code of the task and any dependency data objects loaded into the instance). 
     Although the virtual machine instances  150  are described here as being assigned to a particular task, in some embodiments, the instances may be assigned to a group of tasks, such that the instance is tied to the group of tasks and any tasks of the group can be executed within the instance. For example, the tasks in the same group may belong to the same security group (e.g., based on their security credentials) such that executing one task in a container on a particular instance  150  after another task has been executed in another container on the same instance does not pose security risks. As discussed below, a task may be associated with permissions encompassing a variety of aspects controlling how a task may execute. For example, permissions of a task may define what network connections (if any) can be initiated by an execution environment of the task. As another example, permissions of a task may define what authentication information is passed to a task, controlling what network-accessible resources are accessible to execution of a task (e.g., objects on the service  160 ). In one embodiment, a security group of a task is based on one or more such permissions. For example, a security group may be defined based on a combination of permissions to initiate network connections and permissions to access network resources. As another example, the tasks of the group may share common dependencies, such that an environment used to execute one task of the group can be rapidly modified to support execution of another task within the group. 
     Once a triggering event to execute a task has been successfully processed by a frontend  130 , the frontend  130  passes a request to a worker manager  140  to execute the task. In one embodiment, each frontend  130  may be associated with a corresponding worker manager  140  (e.g., a worker manager  140  co-located or geographically nearby to the frontend  130 ) and thus, the frontend  130  may pass most or all requests to that worker manager  140 . In another embodiment, a frontend  130  may include a location selector configured to determine a worker manager  140  to which to pass the execution request. In one embodiment, the location selector may determine the worker manager  140  to receive a call based on hashing the call, and distributing the call to a worker manager  140  selected based on the hashed value (e.g., via a hash ring). Various other mechanisms for distributing calls between worker managers  140  will be apparent to one of skill in the art. 
     Thereafter, the worker manager  140  may modify a virtual machine instance  150  (if necessary) and execute the code of the task within the instance  150 . As shown in  FIG. 1 , respective instances  150  may have operating systems (OS)  152  (shown as OS  152 A and  152 B), language runtimes  154  (shown as runtime  154 A and  154 B), and user code  156  (shown as user code  156 A and  156 B). The OS  152 , runtime  154 , and user code  156  may collectively enable execution of the user code to implement the task. Thus, via operation of the on-demand code execution system  120 , tasks may be rapidly executed within an execution environment. 
     In accordance with aspects of the present disclosure, each VM  150  additionally includes staging code  157  executable to facilitate staging of input data on the VM  150  and handling of output data written on the VM  150 , as well as a VM data store  158  accessible through a local file system of the VM  150 . Illustratively, the staging code  157  represents a process executing on the VM  150  (or potentially a host device of the VM  150 ) and configured to obtain data from the object storage service  160  and place that data into the VM data store  158 . The staging code  157  can further be configured to obtain data written to a file within the VM data store  158 , and to transmit that data to the object storage service  160 . Because such data is available at the VM data store  158 , user code  156  is not required to obtain data over a network, simplifying user code  156  and enabling further restriction of network communications by the user code  156 , thus increasing security. Rather, as discussed above, user code  156  may interact with input data and output data as files on the VM data store  158 , by use of file handles passed to the code  156  during an execution. In some embodiments, input and output data may be stored as files within a kernel-space file system of the data store  158 . In other instances, the staging code  157  may provide a virtual file system, such as a filesystem in userspace (FUSE) interface, which provides an isolated file system accessible to the user code  156 , such that the user code&#39;s access to the VM data store  158  is restricted. 
     As used herein, the term “local file system” generally refers to a file system as maintained within an execution environment, such that software executing within the environment can access data as file, rather than via a network connection. In accordance with aspects of the present disclosure, the data storage accessible via a local file system may itself be local (e.g., local physical storage), or may be remote (e.g., accessed via a network protocol, like NFS, or represented as a virtualized block device provided by a network-accessible service). Thus, the term “local file system” is intended to describe a mechanism for software to access data, rather than physical location of the data. 
     The VM data store  158  can include any persistent or non-persistent data storage device. In one embodiment, the VM data store  158  is physical storage of the host device, or a virtual disk drive hosted on physical storage of the host device. In another embodiment, the VM data store  158  is represented as local storage, but is in fact a virtualized storage device provided by a network accessible service. For example, the VM data store  158  may be a virtualized disk drive provided by a network-accessible block storage service. In some embodiments, the object storage service  160  may be configured to provide file-level access to objects stored on the data stores  168 , thus enabling the VM data store  158  to be virtualized based on communications between the staging code  157  and the service  160 . For example, the object storage service  160  can include a file-level interface  166  providing network access to objects within the data stores  168  as files. The file-level interface  166  may, for example, represent a network-based file system server (e.g., a network file system (NFS)) providing access to objects as files, and the staging code  157  may implement a client of that server, thus providing file-level access to objects of the service  160 . 
     In some instances, the VM data store  158  may represent virtualized access to another data store executing on the same host device of a VM instance  150 . For example, an active pool  148  may include one or more data staging VM instances (not shown in  FIG. 1 ), which may be co-tenanted with VM instances  150  on the same host device. A data staging VM instance may be configured to support retrieval and storage of data from the service  160  (e.g., data objects or portions thereof, input data passed by client devices  102 , etc.), and storage of that data on a data store of the data staging VM instance. The data staging VM instance may, for example, be designated as unavailable to support execution of user code  156 , and thus be associated with elevated permissions relative to instances  150  supporting execution of user code. The data staging VM instance may make this data accessible to other VM instances  150  within its host device (or, potentially, on nearby host devices), such as by use of a network-based file protocol, like NFS. Other VM instances  150  may then act as clients to the data staging VM instance, enabling creation of virtualized VM data stores  158  that, from the point of view of user code  156 A, appear as local data stores. Beneficially, network-based access to data stored at a data staging VM can be expected to occur very quickly, given the co-location of a data staging VM and a VM instance  150  within a host device or on nearby host devices. 
     While some examples are provided herein with respect to use of IO stream handles to read from or write to a VM data store  158 , IO streams may additionally be used to read from or write to other interfaces of a VM instance  150  (while still removing a need for user code  156  to conduct operations other than stream-level operations, such as creating network connections). For example, staging code  157  may “pipe” input data to an execution of user code  156  as an input stream, the output of which may be “piped” to the staging code  157  as an output stream. As another example, a staging VM instance or a hypervisor to a VM instance  150  may pass input data to a network port of the VM instance  150 , which may be read-from by staging code  157  and passed as an input stream to the user code  157 . Similarly, data written to an output stream by the task code  156  may be written to a second network port of the instance  150 A for retrieval by the staging VM instance or hypervisor. In yet another example, a hypervisor to the instance  150  may pass input data as data written to a virtualized hardware input device (e.g., a keyboard) and staging code  157  may pass to the user code  156  a handle to the IO stream corresponding to that input device. The hypervisor may similarly pass to the user code  156  a handle for an IO stream corresponding to an virtualized hardware output device, and read data written to that stream as output data. Thus, the examples provided herein with respect to file streams may generally be modified to relate to any IO stream. 
     The object storage service  160  and on-demand code execution system  120  are depicted in  FIG. 1  as operating in a distributed computing environment including several computer systems that are interconnected using one or more computer networks (not shown in  FIG. 1 ). The object storage service  160  and on-demand code execution system  120  could also operate within a computing environment having a fewer or greater number of devices than are illustrated in  FIG. 1 . Thus, the depiction of the object storage service  160  and on-demand code execution system  120  in  FIG. 1  should be taken as illustrative and not limiting to the present disclosure. For example, the on-demand code execution system  120  or various constituents thereof could implement various Web services components, hosted or “cloud” computing environments, or peer to peer network configurations to implement at least a portion of the processes described herein. In some instances, the object storage service  160  and on-demand code execution system  120  may be combined into a single service. Further, the object storage service  160  and on-demand code execution system  120  may be implemented directly in hardware or software executed by hardware devices and may, for instance, include one or more physical or virtual servers implemented on physical computer hardware configured to execute computer executable instructions for performing various features that will be described herein. The one or more servers may be geographically dispersed or geographically co-located, for instance, in one or more data centers. In some instances, the one or more servers may operate as part of a system of rapidly provisioned and released computing resources, often referred to as a “cloud computing environment.” 
     In the example of  FIG. 1 , the object storage service  160  and on-demand code execution system  120  are illustrated as connected to the network  104 . In some embodiments, any of the components within the object storage service  160  and on-demand code execution system  120  can communicate with other components of the on-demand code execution system  120  via the network  104 . In other embodiments, not all components of the object storage service  160  and on-demand code execution system  120  are capable of communicating with other components of the virtual environment  100 . In one example, only the frontends  130  and  162  (which may in some instances represent multiple frontends) may be connected to the network  104 , and other components of the object storage service  160  and on-demand code execution system  120  may communicate with other components of the environment  100  via the respective frontends  130  and  162 . 
     While some functionalities are generally described herein with reference to an individual component of the object storage service  160  and on-demand code execution system  120 , other components or a combination of components may additionally or alternatively implement such functionalities. For example, while the object storage service  160  is depicted in  FIG. 1  as including an object manipulation engine  170 , functions of that engine  170  may additionally or alternatively be implemented as tasks on the on-demand code execution system  120 . Moreover, while the on-demand code execution system  120  is described as an example system to apply data manipulation tasks, other compute systems may be used to execute user-defined tasks, which compute systems may include more, fewer or different components than depicted as part of the on-demand code execution system  120 . In a simplified example, the object storage service  160  may include a physical computing device configured to execute user-defined tasks on demand, thus representing a compute system usable in accordance with embodiments of the present disclosure. Thus, the specific configuration of elements within  FIG. 1  is intended to be illustrative. 
       FIG. 2  depicts a general architecture of a frontend server  200  computing device implementing a frontend  162  of  FIG. 1 . The general architecture of the frontend server  200  depicted in  FIG. 2  includes an arrangement of computer hardware and software that may be used to implement aspects of the present disclosure. The hardware may be implemented on physical electronic devices, as discussed in greater detail below. The frontend server  200  may include many more (or fewer) elements than those shown in  FIG. 2 . It is not necessary, however, that all of these generally conventional elements be shown in order to provide an enabling disclosure. Additionally, the general architecture illustrated in  FIG. 2  may be used to implement one or more of the other components illustrated in  FIG. 1 . 
     As illustrated, the frontend server  200  includes a processing unit  290 , a network interface  292 , a computer readable medium drive  294 , and an input/output device interface  296 , all of which may communicate with one another by way of a communication bus. The network interface  292  may provide connectivity to one or more networks or computing systems. The processing unit  290  may thus receive information and instructions from other computing systems or services via the network  104 . The processing unit  290  may also communicate to and from primary memory  280  or secondary memory  298  and further provide output information for an optional display (not shown) via the input/output device interface  296 . The input/output device interface  296  may also accept input from an optional input device (not shown). 
     The primary memory  280  or secondary memory  298  may contain computer program instructions (grouped as units in some embodiments) that the processing unit  290  executes in order to implement one or more aspects of the present disclosure. These program instructions are shown in  FIG. 2  as included within the primary memory  280 , but may additionally or alternatively be stored within secondary memory  298 . The primary memory  280  and secondary memory  298  correspond to one or more tiers of memory devices, including (but not limited to) RAM, 3D XPOINT memory, flash memory, magnetic storage, and the like. The primary memory  280  is assumed for the purposes of description to represent a main working memory of the worker manager  140 , with a higher speed but lower total capacity than secondary memory  298 . 
     The primary memory  280  may store an operating system  284  that provides computer program instructions for use by the processing unit  290  in the general administration and operation of the frontend server  200 . The memory  280  may further include computer program instructions and other information for implementing aspects of the present disclosure. For example, in one embodiment, the memory  280  includes a user interface unit  282  that generates user interfaces (or instructions therefor) for display upon a computing device, e.g., via a navigation or browsing interface such as a browser or application installed on the computing device. 
     In addition to or in combination with the user interface unit  282 , the memory  280  may include a control plane unit  286  and data plane unit  288  each executable to implement aspects of the present disclosure. Illustratively, the control plane unit  286  may include code executable to enable owners of data objects or collections of objects to attach manipulations, serverless functions, or data processing pipelines to an I/O path, in accordance with embodiments of the present disclosure. For example, the control plane unit  286  may enable the frontend  162  to implement the interactions of  FIG. 3 . The data plane unit  288  may illustratively include code enabling handling of I/O operations on the object storage service  160 , including implementation of manipulations, serverless functions, or data processing pipelines attached to an I/O path (e.g., via the interactions of  FIGS. 5A-6B , implementation of the routines of  FIGS. 7-8 , etc.). 
     The frontend server  200  of  FIG. 2  is one illustrative configuration of such a device, of which others are possible. For example, while shown as a single device, a frontend server  200  may in some embodiments be implemented as multiple physical host devices. Illustratively, a first device of such a frontend server  200  may implement the control plane unit  286 , while a second device may implement the data plane unit  288 . 
     While described in  FIG. 2  as a frontend server  200 , similar components may be utilized in some embodiments to implement other devices shown in the environment  100  of  FIG. 1 . For example, a similar device may implement a worker manager  140 , as described in more detail in U.S. Pat. No. 9,323,556, entitled “PROGRAMMATIC EVENT DETECTION AND MESSAGE GENERATION FOR REQUESTS TO EXECUTE PROGRAM CODE,” and filed Sep. 30, 2014 (the “&#39;556 Patent”), the entirety of which is hereby incorporated by reference. 
     With reference to  FIG. 3 , illustrative interactions are depicted for enabling a client device  102 A to modify an I/O path for one or more objects on an object storage service  160  by inserting a data manipulation into the I/O path, which manipulation is implemented within a task executable on the on-demand code execution system  120 . 
     The interactions of  FIG. 3  begin at ( 1 ), where the client device  102 A authors the stream manipulation code. The code can illustratively function to access an input file handle provided on execution of the program (which may, for example, be represented by the standard input stream for a program, commonly “stdin”), perform manipulations on data obtained from that file handle, and write data to an output file handle provided on execution of the program (which may, for example, by represented by the standard output stream for a program, commonly “stdout”). 
     While examples are discussed herein with respect to a “file” handle, embodiments of the present disclosure may utilize handles providing access to any operating-system-level input/output (IO) stream, examples of which include byte streams, character streams, file streams, and the like. As used herein, the term operating-system-level input/output stream (or simply an “IO stream”) is intended to refer to a stream of data for which an operating system provides a defined set of functions, such as seeking within the stream, reading from a stream, and writing to a stream. Streams may be created in various manners. For example, a programming language may generate a stream by use of a function library to open a file on a local operating system, or a stream may be created by use of a “pipe” operator (e.g., within an operating system shell command language). As will be appreciated by one skilled in the art, most general purpose programming languages include, as basic functionality of the code, the ability to interact with streams. 
     In accordance with embodiments of the present disclosure, task code may be authored to accept, as a parameter of the code, an input handle and an output handle, both representing IO streams (e.g., an input stream and an output stream, respectively). The code may then manipulate data of the input stream, and write an output to the output stream. Given use of a general purpose programming language, any of a variety of functions may be implemented according to the desires of the user. For example, a function may search for and remove confidential information from the input stream. While some code may utilize only input and output handles, other code may implement additional interfaces, such as network communication interfaces. However, by providing the code with access to input and output streams (via respective handles) created outside of the code, the need for the code to create such streams is removed. Moreover, because streams may be created outside of the code, and potentially outside of an execution environment of the code, stream manipulation code need not necessarily be trusted to conduct certain operations that may be necessary to create a stream. For example, a stream may represent information transmitted over a network connection, without the code being provided with access to that network connection. Thus, use of IO streams to pass data into and out of code executions can simplify code while increasing security. 
     As noted above, the code may be authored in a variety of programming languages. Authoring tools for such languages are known in the art and thus will not be described herein. While authoring is described in  FIG. 3  as occurring on the client device  102 A, the service  160  may in some instances provide interfaces (e.g., web GUIs) through which to author or select code. 
     At ( 2 ), the client device  102 A submits the stream manipulation code to the frontend  162  of the service  160 , and requests that an execution of the code be inserted into an I/O path for one or more objects. Illustratively, the frontends  162  may provide one or more interfaces to the device  102 A enabling submission of the code (e.g., as a compressed file). The frontends  162  may further provide interfaces enabling designation of one or more I/O paths to which an execution of the code should be applied. Each I/O path may correspond, for example, to an object or collection of objects (e.g., a “bucket” of objects). In some instances, an I/O path may further corresponding to a given way of accessing such object or collection (e.g., a URI through which the object is created), to one or more accounts attempting to access the object or collection, or to other path criteria. Designation of the path modification is then stored in the I/O path modification data store  164 , at ( 3 ). Additionally, the stream manipulation code is stored within the object data stores  166  at ( 4 ). 
     As such, when an I/O request is received via the specified I/O path, the service  160  is configured to execute the stream manipulation code against input data for the request (e.g., data provided by the client device  102 A or an object of the service  160 , depending on the I/O request), before then applying the request to the output of the code execution. In this manner, a client device  102 A (which in  FIG. 3  illustratively represents an owner of an object or object collection) can obtain greater control over data stored on and retrieved from the object storage service  160 . 
     The interactions of  FIG. 3  generally relate to insertion of a single data manipulation into the I/O path of an object or collection on the service  160 . However, in some embodiments of the present disclosure an owner of an object or collection is enabled to insert multiple data manipulations into such an I/O path. Each data manipulation may correspond, for example, to a serverless code-based manipulation or a native manipulation of the service  160 . For example, assume an owner has submitted a data set to the service  160  as an object, and that the owner wishes to provide an end user with a filtered view of a portion of that data set. While the owner could store that filtered view of the portion as a separate object and provide the end user with access to that separate object, this results in data duplication on the service  160 . In the case that the owner wishes to provide multiple end users with different portions of the data set, potentially with customized filters, that data duplication grows, resulting in significant inefficiencies. In accordance with the present disclosure, another option may be for the owner to author or obtain custom code to implement different filters on different portions of the object, and to insert that code into the I/O path for the object. However, this approach may require the owner to duplicate some native functionality of the service  160  (e.g., an ability to retrieve a portion of a data set). Moreover, this approach would inhibit modularity and reusability of code, since a single set of code would be required to conduct two functions (e.g., selecting a portion of the data and filtering that portion). 
     To address these shortcomings, embodiments of the present disclosure enable an owner to create a pipeline of data manipulations to be applied to an I/O path, linking together multiple data manipulations, each of which may also be inserted into other I/O paths. An illustrative visualization of such a pipeline is shown in  FIG. 4  as pipeline  400 . Specifically, the pipeline  400  illustrates a series of data manipulations that an owner specifies are to occur on calling of a request method against an object or object collection. As shown in  FIG. 4 , the pipeline begins with input data, specified within the call according to a called request method. For example, a PUT call may generally include the input data as the data to be stored, while a GET call may generally include the input data by reference to a stored object. A LIST call may specify a directory, a manifest of which is the input data to the LIST request method. 
     Contrary to typical implementations of request methods, in the illustrative pipeline  400 , the called request method is not initially applied to the input data. Rather, the input data is initially passed to an execution of “code A”  404 , where code A represents a first set of user-authored code. The output of that execution is then passed to “native function A”  406 , which illustratively represents a native function of the service  160 , such as a “SELECT” or byte-range function implemented by the object manipulation engine  170 . The output of that native function  406  is then passed to an execution of “code B”  408 , which represents a second set of user-authored code. Thereafter, the output of that execution  408  is passed to the called request method  410  (e.g., GET, PUT, LIST, etc.). Accordingly, rather than the request method being applied to the input data as in conventional techniques, in the illustration of  FIG. 4 , the request method is applied to the output of the execution  408 , which illustratively represents a transformation of the input data according to one or more owner-specified manipulations  412 . Notably, implementation of the pipeline  400  may not require any action or imply any knowledge of the pipeline  400  on the part of a calling client device  102 . As such, implementation of pipelines can be expected not to impact existing mechanisms of interacting with the service  160  (other than altering the data stored on or retrieved from the service  160  in accordance with the pipeline). For example, implementation of a pipeline can be expected not to require reconfiguration of existing programs utilizing an API of the service  160 . 
     While the pipeline  400  of  FIG. 4  is linear, in some embodiments the service  160  may enable an owner to configure non-linear pipelines, such as by including conditional or branching nodes within the pipeline. Illustratively, as described in more detail below, data manipulations (e.g., serverless-based functions) can be configured to include a return value, such as an indication of successful execution, encountering an error, etc. In one example, the return value of a data manipulation may be used to select a conditional branch within a branched pipeline, such that a first return value causes the pipeline to proceed on a first branch, while a second return value causes the pipeline to proceed on a second branch. In some instances, pipelines may include parallel branches, such that data is copied or divided to multiple data manipulations, the outputs of which are passed to a single data manipulation for merging prior to executing the called method. The service  160  may illustratively provide a graphical user interface through which owners can create pipelines, such as by specifying nodes within the pipeline, specifying one or more parameters that should automatically be applied to a data manipulation corresponding to a node, specifying whether a user should supply one or more parameters for a data manipulation corresponding to a node, and linking those nodes together via logical connections. A variety of flow-based development interfaces are known and may be utilized in conjunction with aspects of the present disclosure. 
     Furthermore, in some embodiments, a pipeline applied to a particular I/O path may be generated on-the-fly, at the time of a request, based on data manipulations applied to the path according to different criteria. For example, an owner of a data collection may apply a first data manipulation to all interactions with objects within a collection, and a second data manipulation to all interactions obtained via a given URI. Thus, when a request is received to interact with an object within the collection and via the given URI, the service  160  may generate a pipeline combining the first and second data manipulations. The service  160  may illustratively implement a hierarchy of criteria, such that manipulations applied to objects are placed within the pipeline prior to manipulations applied to a URI, etc. 
     In some embodiments, client devices  102  may be enabled to request inclusion of a data manipulation within a pipeline. For example, within parameters of a GET request, a client device  102  may specify a particular data manipulation to be included within a pipeline applied in connection with the request. Illustratively, a collection owner may specify one or more data manipulations allowed for the collection, and further specify identifiers for those manipulations (e.g., function names). Thus, when requesting to interact with the collection, a client device  102  may specify the identifier to cause the manipulation to be included within a pipeline applied to the I/O path. In one embodiment, client-requested manipulations are appended to the end of a pipeline subsequent to owner-specified data manipulations and prior to implementing the requested request method. For example, where a client device  102  requests to GET a data set, and requests that a search function by applied to the data set before the GET method is implemented, the search function can receive as input data the output of an owner-specified data manipulations for the data set (e.g., manipulations to remove confidential information from the data set). In addition, requests may in some embodiments specify parameters to be passed to one or more data manipulations (whether specified within the request or not). Accordingly, while embodiments of the present disclosure can enable data manipulations without knowledge of those manipulations on the part of client devices  102 , other embodiments may enable client devices  102  to pass information within an I/O request for use in implementing data manipulations. 
     Moreover, while example embodiments of the present disclosure are discussed with respect to manipulation of input data to a called method, embodiments of the present disclosure may further be utilized to modify aspects of a request, including a called method. For example, a serverless task execution may be passed the content of a request (including, e.g., a called method and parameters) and be configured to modify and return, as a return value to a frontend  162 , a modified version of the method or parameters. Illustratively, where a client device  102  is authenticated as a user with access to only a portion of a data object, a serverless task execution may be passed a call to “GET” that data object, and may transform parameters of the GET request such that it applies only to a specific byte range of the data object corresponding to the portion that the user may access. As a further example, tasks may be utilized to implement customized parsing or restrictions on called methods, such as by limiting the methods a user may call, the parameters to those methods, or the like. In some instances, application of one or more functions to a request (e.g., to modify the method called or method parameters) may be viewed as a “pre-data processing” pipeline, and may thus be implemented prior to obtaining the input data within the pipeline  400  (which input data may change due to changes in the request), or may be implemented independently of a data manipulation pipeline  400 . 
     Similarly, while example embodiments of the present disclosure are discussed with respect to application of a called method to output data of one or more data manipulations, in some embodiments manipulations can additionally or alternatively occur after application of a called method. For example, a data object may contain sensitive data that a data owner desires to remove prior to providing the data to a client. The owner may further enable a client to specify native manipulations to the data set, such as conducting a database query on the dataset (e.g., via a SELECT resource method). While the owner may specify a pipeline for the data set to cause filtering of sensitive data to be conducted prior to application of the SELECT method, such an order of operations may be undesirable, as filtering may occur with respect to the entire data object rather than solely the portion returned by the SELECT query. Accordingly, additionally or alternatively to specifying manipulations that occur prior to satisfying a request method, embodiments of the present disclosure can enable an owner to specify manipulations to occur subsequent to application of a called method but prior to conducting a final operation to satisfy a request. For example, in the case of a SELECT operation, the service  160  may first conduct the SELECT operation against specified input data (e.g., a data object), and then pass the output of that SELECT operation to a data manipulation, such as a serverless task execution. The output of that execution can then be returned to a client device  102  to satisfy the request. 
     While  FIG. 3  and  FIG. 4  are generally described with reference to serverless tasks authored by an owner of an object or collection, in some instances the service  160  may enable code authors to share their tasks with other users of the service  160 , such that code of a first user is executed in the I/O path of an object owned by a second user. The service  160  may also provide a library of tasks for use by each user. In some cases, the code of a shared task may be provided to other users. In other cases, the code of the shared task may be hidden from other users, such that the other users can execute the task but not view code of the task. In these cases, other users may illustratively be enabled to modify specific aspects of code execution, such as the permissions under which the code will execute. 
     With reference to  FIGS. 5A and 5B , illustrative interactions will be discussed for applying a modification to an I/O path for a request to store an object on the service  160 , which request is referred to in connection with these figures as a “PUT” request or “PUT object call.” While shown in two figures, numbering of interactions is maintained across  FIGS. 5A and 5B . 
     The interactions begin at ( 1 ), where a client device  102 A submits a PUT object call to the storage service  160 , corresponding to a request to store input data (e.g., included or specified within the call) on the service  160 . The input data may correspond, for example, to a file stored on the client device  102 A. As shown in  FIG. 5A , the call is directed to a frontend  162  of the service  160  that, at ( 2 ), retrieves from the I/O path modification data store  164  an indication of modifications to the I/O path for the call. The indication may reflect, for example, a pipeline to be applied to calls received on the I/O path. The I/O path for a call may generally be specified with respect to a request method included within a call, an object or collection of objects indicated within the call, a specific mechanism of reaching the service  160  (e.g., protocol, URI used, etc.), an identity or authentication status of the client device  102 A, or a combination thereof. For example, in  FIG. 5A , the I/O path used can correspond to use of a PUT request method directed to a particular URI (e.g., associated with the frontend  162 ) to store an object in a particular logical location on the service  160  (e.g., a specific bucket). In  FIGS. 5A and 5B , it is assumed that an owner of that logical location has previously specified a modification to the I/O path, and specifically, has specified that a serverless function should be applied to the input data before a result of that function is stored in the service  160 . 
     Accordingly, at ( 3 ), the frontend  162  detects within the modifications for the I/O path inclusion of a serverless task execution. Thus, at ( 4 ), the frontend  162  submits a call to the on-demand code execution system  120  to execute the task specified within the modifications against the input data specified within the call. 
     The on-demand code execution system  120 , at ( 5 ), therefore generates an execution environment  502  in which to execute code corresponding to the task. Illustratively, the call may be directed to a frontend  130  of the system  120 , which may distribute instructions to a worker manager  140  to select or generate a VM instance  150  in which to execute the task, which VM instance  150  illustratively represents the execution environment  502 . During generation of the execution environment  502 , the system  120  further provisions the environment with code  504  of the task indicated within the I/O path modification (which may be retrieved, for example, from the object data stores  168 ). While not shown in  FIG. 5A , the environment  502  further includes other dependencies of the code, such as access to an operating system, a runtime required to execute the code, etc. 
     In some embodiments, generation of the execution environment  502  can include configuring the environment  502  with security constraints limiting access to network resources. Illustratively, where a task is intended to conduct data manipulation without reference to network resources, the environment  502  can be configured with no ability to send or receive information via a network. Where a task is intended to utilize network resources, access to such resources can be provided on a “whitelist” basis, such that network communications from the environment  502  are allowed only for specified domains, network addresses, or the like. Network restrictions may be implemented, for example, by a host device hosting the environment  502  (e.g., by a hypervisor or host operating system). In some instances, network access requirements may be utilized to assist in placement of the environment  502 , either logically or physically. For example, where a task requires no access to network resources, the environment  502  for the task may be placed on a host device that is distant from other network-accessible services of the service provider system  110 , such as an “edge” device with a lower-quality communication channel to those services. Where a task requires access to otherwise private network services, such as services implemented within a virtual private cloud (e.g., a local-area-network-like environment implemented on the service  160  on behalf of a given user), the environment  502  may be created to exist logically within that cloud, such that a task execution  502  accesses resources within the cloud. In some instances, a task may be configured to execute within a private cloud of a client device  102  that submits an I/O request. In other instances, a task may be configured to execute within a private cloud of an owner of the object or collection referenced within the request. 
     In addition to generating the environment  502 , at ( 6 ), the system  120  provisions the environment with stream-level access to an input file handle  506  and an output file handle  508 , usable to read from and write to the input data and output data of the task execution, respectively. In one embodiment, file handles  506  and  508  may point to a (physical or virtual) block storage device (e.g., disk drive) attached to the environment  502 , such that the task can interact with a local file system to read input data and write output data. For example, the environment  502  may represent a virtual machine with a virtual disk drive, and the system  120  may obtain the input data from the service  160  and store the input data on the virtual disk drive. Thereafter, on execution of the code, the system  120  may pass to the code a handle of the input data as stored on the virtual disk drive, and a handle of a file on the drive to which to write output data. In another embodiment, file handles  506  and  508  may point to a network file system, such as an NFS-compatible file system, on which the input data has been stored. For example, the frontend  162  during processing of the call may store the input data as an object on the object data stores  166 , and the file-level interface  166  may provide file-level access to the input data and to a file representing output data. In some cases, the file handles  506  and  508  may point to files on a virtual file system, such as a file system in user space. By providing handles  506  and  508 , the task code  504  is enabled to read the input data and write output data using stream manipulations, as opposed to being required to implement network transmissions. Creation of the handles  506  and  508  (or streams corresponding to the handles) may illustratively be achieved by execution of staging code  157  within or associated with the environment  502 . 
     The interactions of  FIG. 5A  are continued in  FIG. 5B , where the system  120  executes the task code  504 . As the task code  504  may be user-authored, any number of functionalities may be implemented within the code  504 . However, for the purposes of description of  FIGS. 5A and 5B , it will be assumed that the code  504 , when executed, reads input data from the input file handle  506  (which may be passed as a commonly used input stream, such as stdin), manipulates the input data, and writes output data to the output file handle  508  (which may be passed as a commonly used output stream, such as stdout). Accordingly, at ( 8 ), the system  120  obtains data written to the output file (e.g., the file referenced in the output file handle) as output data of the execution. In addition, at ( 9 ), the system  120  obtains a return value of the code execution (e.g., a value passed in a final call of the function). For the purposes of description of  FIGS. 5A and 5B , it will be assumed that the return value indicates success of the execution. At ( 10 ), the output data and the success return value are then passed to the frontend  162 . 
     While shown as a single interaction in  FIG. 5B , in some embodiments output data of a task execution and a return value of that execution may be returned separately. For example, during execution, task code  504  may write to an output file through the handle  508 , and this data may be periodically or iteratively returned to the service  160 . Illustratively, where the output file exists on a file system in user space implemented by staging code, the staging code may detect and forward each write to the output file to the frontend  162 . Where the output file exists on a network file system, writes to the file may directly cause the written data to be transmitted to the interface  166  and thus the service  160 . In some instances, transmitting written data iteratively may reduce the amount of storage required locally to the environment  502 , since written data can, according to some embodiments, be deleted from local storage of the environment  502 . 
     In addition, while a success return value is assumed in  FIGS. 5A and 5B , other types of return value are possible and contemplated. For example, an error return value may be used to indicate to the frontend  162  that an error occurred during execution of task code  504 . As another example, user-defined return values may be used to control how conditional branching within a pipeline proceeds. In some cases, the return value may indicate to the frontend  162  a request for further processing. For example, a task execution may return to the frontend  162  a call to execute another serverless task (potentially not specified within a path modification for the current I/O path). Moreover, return values may specify to the frontend  162  what return value is to be returned to the client device  102 A. For example, a typical PUT request method called at the service  160  may be expected to return an HTTP 200 code (“OK”). As such, a success return value from the task code may further indicate that the frontend  162  should return an HTTP 200 code to the client device  102 A. An error return value may, for example, indicate that the frontend  162  should return a 3XX HTTP redirection or 4XX HTTP error code to the client device  102 A. Still further, in some cases, return values may specify to the frontend  162  content of a return message to the client device  102 A other than a return value. For example, the frontend  162  may be configured to return a given HTTP code (e.g.,  200 ) for any request from the client device  102 A that is successfully retrieved at the frontend  162  and invokes a data processing pipeline. A task execution may then be configured to specify, within its return value, data to be passed to the client device  102 A in addition to that HTTP code. Such data may illustratively include structured data (e.g., extensible markup language (XML) data) providing information generated by the task execution, such as data indicating success or failure of the task. This approach may beneficially enable the frontend  162  to quickly respond to requests (e.g., without awaiting execution of a task) while still enabling a task execution to pass information to the client device  102 . 
     For purposes of the present illustration, it will be assumed that the success return value of the task indicates that an HTTP 2XX success response should be passed to the device  102 A. Accordingly, on receiving output data, the frontend  162  stores the output data as an object within the object data stores  168 , ( 11 ). Interaction ( 11 ) illustratively corresponds to implementation of the PUT request method, initially called for by the client device  102 A, albeit by storing the output of the task execution rather than the provided input data. After implementing the called PUT request method, the frontend  162 , at ( 12 ), returns to the client device  102 A the success indicator indicated by the success return value of the task (e.g., an HTTP 200 response code). Thus, from the perspective of the client device  102 A, a call to PUT an object on the storage service  160  resulted in creation of that object on the service  160 . However, rather than storing the input data provided by the device  102 A, the object stored on the service  160  corresponds to output data of an owner-specified task, thus enabling the owner of the object greater control over the contents of that object. In some use cases, the service  160  may additionally store the input data as an object (e.g., where the owner-specified task corresponds to code executable to provide output data usable in conjunction with the input data, such as checksum generated from the input data). 
     With reference to  FIGS. 6A and 6B , illustrative interactions will be discussed for applying a modification to an I/O path for a request to retrieve an object on the service  160 , which request is referred to in connection with these figures as a “GET” request or “GET call.” While shown in two figures, numbering of interactions is maintained across  FIGS. 6A and 6B . 
     The interactions begin at ( 1 ), where a client device  102 A submits a GET call to the storage service  160 , corresponding to a request to obtain data of an object (identified within the call) stored on the service  160 . As shown in  FIG. 6A , the call is directed to a frontend  162  of the service  160  that, at ( 2 ), retrieves from the I/O path modification data store  164  an indication of modifications to the I/O path for the call. For example, in  FIG. 6A , the I/O path used can correspond to use of a GET request method directed to a particular URI (e.g., associated with the frontend  162 ) to retrieve an object in a particular logical location on the service  160  (e.g., a specific bucket). In  FIGS. 6A and 6B , it is assumed that an owner of that logical location has previously specified a modification to the I/O path, and specifically, has specified that a serverless function should be applied to the object before a result of that function is returned to the device  102 A as the requested object. 
     Accordingly, at ( 3 ), the frontend  162  detects within the modifications for the I/O path inclusion of a serverless task execution. Thus, at ( 4 ), the frontend  162  submits a call to the on-demand code execution system  120  to execute the task specified within the modifications against the object specified within the call. The on-demand code execution system  120 , at ( 5 ), therefore generates an execution environment  502  in which to execute code corresponding to the task. Illustratively, the call may be directed to a frontend  130  of the system, which may distribute instructions to a worker manager  140  to select or generate a VM instance  150  in which to execute the task, which VM instance  150  illustratively represents the execution environment  502 . During generation of the execution environment  502 , the system  120  further provisions the environment with code  504  of the task indicated within the I/O path modification (which may be retrieved, for example, from the object data stores  168 ). While not shown in  FIG. 6A , the environment  502  further includes other dependencies of the code, such as access to an operating system, a runtime required to execute the code, etc. 
     In addition, at ( 6 ), the system  120  provisions the environment with stream-level access to an input file handle  506  and an output file handle  508 , usable to read from and write to the input data (the object) and output data of the task execution, respectively. As discussed above, file handles  506  and  508  may point to a (physical or virtual) block storage device (e.g., disk drive) attached to the environment  502 , such that the task can interact with a local file system to read input data and write output data. For example, the environment  502  may represent a virtual machine with a virtual disk drive, and the system  120  may obtain the object referenced within the call from the service  160 , at ( 6 ′), and store the object on the virtual disk drive. Thereafter, on execution of the code, the system  120  may pass to the code a handle of the object as stored on the virtual disk drive, and a handle of a file on the drive to which to write output data. In another embodiment, file handles  506  and  508  may point to a network file system, such as an NFS-compatible file system, on which the object has been stored. For example, the file-level interface  166  may provide file-level access to the object as stored within the object data stores, as well as to a file representing output data. By providing handles  506  and  508 , the task code  504  is enabled to read the input data and write output data using stream manipulations, as opposed to being required to implement network transmissions. Creation of the handles  506  and  508  may illustratively be achieved by execution of staging code  157  within or associated with the environment  502 . 
     The interactions of  FIG. 6A  are continued in  FIG. 6B , where the system  120  executes the task code  504  at ( 7 ). As the task code  504  may be user-authored, any number of functionalities may be implemented within the code  504 . However, for the purposes of description of  FIGS. 6A and 6B , it will be assumed that the code  504 , when executed, reads input data (corresponding to the object identified within the call) from the input file handle  506  (which may be passed as a commonly used input stream, such as stdin), manipulates the input data, and writes output data to the output file handle  508  (which may be passed as a commonly used output stream, such as stdout). Accordingly, at ( 8 ), the system  120  obtains data written to the output file (e.g., the file referenced in the output file handle) as output data of the execution. In addition, at ( 9 ), the system  120  obtains a return value of the code execution (e.g., a value passed in a final call of the function). For the purposes of description of  FIGS. 6A and 6B , it will be assumed that the return value indicates success of the execution. At ( 10 ), the output data and the success return value are then passed to the frontend  162 . 
     On receiving output data and the return value, the frontend  162  returns the output data of the task execution as the requested object. Interaction ( 11 ) thus illustratively corresponds to implementation of the GET request method, initially called for by the client device  102 A, albeit by returning the output of the task execution rather than the object specified within the call. From the perspective of the client device  102 A, a call to GET an object from the storage service  160  therefore results in return of data to the client device  102 A as the object. However, rather than returning the object as stored on the service  160 , the data provided to the client device  102 A corresponds to output data of an owner-specified task, thus enabling the owner of the object greater control over the data returned to the client device  102 A. 
     Similarly to as discussed above with respect to  FIGS. 5A and 5B , while shown as a single interaction in  FIG. 6B , in some embodiments output data of a task execution and a return value of that execution may be returned separately. In addition, while a success return value is assumed in  FIGS. 6A and 6B , other types of return value are possible and contemplated, such as error values, pipeline-control values, or calls to execute other data manipulations. Moreover, return values may indicate what return value is to be returned to the client device  102 A (e.g., as an HTTP status code). In some instances, where output data is iteratively returned from a task execution, the output data may also be iteratively provided by the frontend  162  to the client device  102 A. Where output data is large (e.g., on the order of hundreds of megabytes, gigabytes, etc.), iteratively returning output data to the client device  102 A can enable that data to be provided as a stream, thus speeding delivery of the content to the device  102 A relative to delaying return of the data until execution of the task completes. 
     While illustrative interactions are described above with reference to  FIGS. 5A-6B , various modifications to these interactions are possible and contemplated herein. For example, while the interactions described above relate to manipulation of input data, in some embodiments a serverless task may be inserted into the I/O path of the service  160  to perform functions other than data manipulation. Illustratively, a serverless task may be utilized to perform validation or authorization with respect to a called request method, to verify that a client device  102 A is authorized to perform the method. Task-based validation or authorization may enable functions not provided natively by the service  160 . For example, consider a collection owner who wishes to limit certain client devices  102  to accessing only objects in the collection created during a certain time range (e.g., the last 30 days, any time excluding the last 30 days, etc.). While the service  160  may natively provide authorization on a per-object or per-collection basis, the service  160  may in some cases not natively provide authorization on a duration-since-creation basis. Accordingly, embodiments of the present disclosure enable the owner to insert into an I/O path to the collection (e.g., a GET path using a given URI to the collection) a serverless task that determines whether the client is authorized to retrieve a requested object based on a creation time of that object. Illustratively, the return value provided by an execution of the task may correspond to an “authorized” or “unauthorized” response. In instances where a task does not perform data manipulation, it may be unnecessary to provision an environment of the task execution with input and output stream handles. Accordingly, the service  160  and system  120  can be configured to forego provisioning the environment with such handles in these cases. Whether a task implements data manipulation may be specified, for example, on creation of the task and stored as metadata for the task (e.g., within the object data stores  166 ). The service  160  may thus determine from that metadata whether data manipulation within the task should be supported by provisioning of appropriate stream handles. 
     While some embodiments may utilize return values without use of stream handles, other embodiments may instead utilize stream handles without use of return values. For example, while the interactions described above relate to providing a return value of a task execution to the storage service  160 , in some instances the system  120  may be configured to detect completion of a function based on interaction with an output stream handle. Illustratively, staging code within an environment (e.g., providing a file system in user space or network-based file system) may detect a call to deallocate the stream handle (e.g., by calling a “file.close( )” function or the like). The staging code may interpret such a call as successful completion of the function, and notify the service  160  of successful completion without requiring the task execution to explicitly provide return value. 
     While the interactions described above generally relate to passing of input data to a task execution, additional or alternative information may be passed to the execution. By way of non-limiting example, such information may include the content of the request from the client device  102  (e.g., the HTTP data transmitted), metadata regarding the request (e.g., a network address from which the request was received or a time of the request), metadata regarding the client device  102  (e.g., an authentication status of the device, account time, or request history), or metadata regarding the requested object or collection (e.g., size, storage location, permissions, or time created, modified, or accessed). Moreover, in addition or as an alternative to manipulation of input data, task executions may be configured to modify metadata regarding input data, which may be stored together with the input data (e.g., within the object) and thus written by way of an output stream handle, or which may be separately stored and thus modified by way of a metadata stream handle, inclusion of metadata in a return value, or separate network transmission to the service  160 . 
     With reference to  FIG. 7 , an illustrative routine  700  for implementing owner-defined functions in connection with an I/O request obtained at the object storage service of  FIG. 1  over an I/O path will be described. The routine  700  may illustratively be implemented subsequent to association of an I/O path (e.g., defined in terms of an object or collection, a mechanism of access to the object or collection, such as a URI, an account transmitting an IO request, etc.) with a pipeline of data manipulations. For example, the routine  700  may be implemented prior to the interactions of  FIG. 3 , discussed above. The routine  700  is illustratively implemented by a frontend  162 . 
     The routine  700  begins at block  702 , where the frontend  162  obtains a request to apply an I/O method to input data. The request illustratively corresponds to a client device (e.g., an end user device). The I/O method may correspond, for example, to an HTTP request method, such as GET, PUT, LIST, DELETE, etc. The input data may be included within the request (e.g., within a PUT request), or referenced in the request (e.g., as an existing object on the object storage service  160 . 
     At block  704 , the frontend  162  determines one or more data manipulations in the I/O path for the request. As noted above, the I/O path may be defined based on a variety of criteria (or combinations thereof), such as the object or collection referenced in the request, a URI through which the request was transmitted, an account associated with the request, etc. Manipulations for each defined I/O path may illustratively be stored at the object storage service  160 . Accordingly, at block  704 , the frontend  162  may compare parameters of the I/O path for the request to stored data manipulations at the object storage service  160  to determine data manipulations inserted into the I/O path. In one embodiment, the manipulations form a pipeline, such as the pipeline  400  of  FIG. 4 , which may be previously stored or constructed by the frontend  162  at block  704  (e.g., by combining multiple manipulations that apply to the I/O path). In some instances, an additional data manipulation may be specified within the request, which data manipulation may be inserted, for example, prior to pre-specified data manipulations (e.g., not specified within the request). In other instances, the request may exclude reference to any data manipulation. 
     At block  706 , the frontend  162  passes input data of the I/O request to an initial data manipulation for the I/O path. The initial data manipulation may include, for example, a native manipulation of the object storage service  160  or a serverless task defined by an owner of the object or collection referenced in the call. Illustratively, where the initial data manipulation is a native manipulation, the frontend  162  may pass the input to the object manipulation engine  170  of  FIG. 1 . Where the initial data manipulation is a serverless task, the frontend  162  can pass the input to the on-demand code execution system  120  of  FIG. 1  for processing via an execution of the task. An illustrative routine for implementing a serverless task is described below with reference to  FIG. 8 . 
     While  FIG. 7  illustratively describes data manipulations, in some instances other processing may be applied to an I/O path by an owner. For example, an owner may insert into an I/O path for an object or collection a serverless task that provides authentication independent of data manipulation. Accordingly, in some embodiments block  706  may be modified such that other data, such as metadata regarding a request or an object specified in the request, is passed to an authentication function or other path manipulation. 
     Thereafter, the routine  700  proceeds to block  708 , where the implementation of the routine  700  varies according to whether additional data manipulations have been associated with the I/O path. If so, the routine  700  proceeds to block  710 , where an output of a prior manipulation is passed to a next manipulation associated with the I/O path (e.g., a subsequent stage of a pipeline). 
     Subsequent to block  710 , the routine  700  then returns to block  708 , until no additional manipulations exist to be implemented. The routine  700  then proceeds to block  712 , where the frontend  162  applies the called I/O method (e.g., GET, PUT, POST, LIST, DELETE, etc.) to the output of the prior manipulation. For example, the frontend  162  may provide the output as a result of a GET or LIST request, or may store the output as a new object as a result of a PUT or POST request. The frontend  162  may further provide a response to the request to a requesting device, such as an indication of success of the routine  700  (or, in cases of failure, failure of the routine). In one embodiment, the response may be determined by a return value provided by a data manipulation implemented at blocks  706  or  710  (e.g., the final manipulation implemented before error or success). For example, a manipulation that indicates an error (e.g., lack of authorization) may specify an HTTP code indicating that error, while a manipulation that proceeds successfully may instruct the frontend  162  to return an HTTP code indicating success, or may instruct the frontend  162  to return a code otherwise associated with application of the I/O method (e.g., in the absence of data manipulations). The routine  700  thereafter ends at block  714 . 
     Notably, application of the called method to that output, as opposed to input specified in an initial request, may alter data stored in or retrieved from the object storage service  160 . For example, data stored on the service  160  as an object may differ from the data submitted within a request to store such data. Similarly, data retrieved from the system as an object may not match the object as stored on the system. Accordingly, implementation of routine  700  enables an owner of data objects to assert greater control over I/O to an object or collection stored on the object storage service  160  on behalf of the owner. 
     In some instances, additional or alternative blocks may be included within the routine  700 , or implementation of such blocks may include additional or alternative operations. For example, as discussed above, in addition to or as an alternative to providing output data, serverless task executions may provide a return value. In some instances, this return value may instruct a frontend  162  as to further actions to take in implementing the manipulation. For example, an error return value may instruct the frontend  162  to halt implementation of manipulations, and provide a specified error value (e.g., an HTTP error code) to a requesting device. Another return value may instruct the frontend  162  to implement an additional serverless task or manipulation. Thus, the routine  700  may in some cases be modified to include, subsequent to blocks  706  and  710  for example, handling of the return value of a prior manipulation (or block  708  may be modified to include handling of such a value). Thus, the routine  700  is intended to be illustrative in nature. 
     With reference to  FIG. 8 , an illustrative routine  800  will be described for executing a task on the on-demand code execution system of  FIG. 1  to enable data manipulations during implementation of an owner-defined function. The routine  800  is illustratively implemented by the on-demand code execution system  120  of  FIG. 1 . 
     The routine  800  begins at block  802 , where the system  120  obtains a call to implement a stream manipulation task (e.g., a task that manipulates data provided as an input IO stream handle). The call may be obtained, for example, in conjunction with blocks  706  or  710  of the routine  700  of  FIG. 7 . The call may include input data for the task, as well as other metadata, such as metadata of a request that preceded the call, metadata of an object referenced within the call, or the like. 
     At block  804 , the system  120  generates an execution environment for the task. Generation of an environment may include, for example, generation of a container or virtual machine instance in which the task may execute and provisioning of the environment with code of the task, as well as any dependencies of the code (e.g., runtimes, libraries, etc.). In one embodiment, the environment is generated with network permissions corresponding to permissions specified for the task. As discussed above, such permissions may be restrictively (as opposed to permissively) set, according to a whitelist for example. As such, absent specification of permissions by an owner of an I/O path, the environment may lack network access. Because the task operates to manipulate streams, rather than network data, this restrictive model can increase security without detrimental effect on functionality. In some embodiments, the environment may be generated at a logical network location providing access to otherwise restricted network resources. For example, the environment may be generated within a virtual private local area network (e.g., a virtual private cloud environment) associated with a calling device. 
     At block  806 , the system  120  stages the environment with an IO stream representing the input data. Illustratively, the system  120  may configure the environment with a file system that includes the input data, and pass to the task code a handle enabling access of the input data as a file stream. For example, the system  120  may configure the environment with a network file system, providing network-based access to the input data (e.g., as stored on the object storage system). In another example, the system  120  may configure the environment with a “local” file system (e.g., from the point of view of an operating system providing the file system), and copy the input data to the local file system. The local file system may, for example, be a filesystem in user space (FUSE). In some instances, the local file system may be implemented on a virtualized disk drive, provided by the host device of the environment or by a network-based device (e.g., as a network-accessible block storage device). In other embodiments, the system  120  may provide the IO stream by “piping” the input data to the execution environment, by writing the input data to a network socket of the environment (which may not provide access to an external network), etc. The system  120  further configures the environment with stream-level access to an output stream, such as by creating a file on the file system for the output data, enabling an execution of the task to create such a file, piping a handle of the environment (e.g., stdout) to a location on another VM instance colocated with the environment or a hypervisor of the environment, etc. 
     At block  808 , the task is executed within the environment. Execution of the task may include executing code of the task, and passing to the execution handles or handles of the input stream and output stream. For example, the system  120  may pass to the execution a handle for the input data, as stored on the file system, as a “stdin” variable. The system may further pass to the execution a handle for the output data stream, e.g., as a “stdout” variable. In addition, the system  120  may pass other information, such as metadata of the request or an object or collection specified within the request, as parameters to the execution. The code of the task may thus execute to conduct stream manipulations on the input data according to functions of the code, and to write an output of the execution to the output stream using 05-level stream operations. 
     The routine  800  then proceeds to block  810 , where the system  120  returns data written to the output stream as output data of the task (e.g., to the frontend  162  of the object storage system). In one embodiment, block  810  may occur subsequent to the execution of the task completing, and as such, the system  120  may return the data written as the complete output data of the task. In other instances, block  810  may occur during execution of the task. For example, the system  120  may detect new data written to the output stream and return that data immediately, without awaiting execution of the task. Illustratively, where the output stream is written to an output file, the system  120  may delete data of the output file after writing, such that sending of new data immediately obviates a need for the file system to maintain sufficient storage to store all output data of the task execution. Still further, in some embodiments, block  810  may occur on detecting a close of the output stream handle describing the output stream. 
     In addition, at block  812 , subsequent to the execution completing, the system  120  returns a return value provided by the execution (e.g., to the frontend  162  of the object storage system). The return value may specify an outcome of the execution, such as success or failure. In some instances, the return value may specify a next action to be undertaken, such as implementation an additional data manipulation. Moreover, the return value may specify data to be provided to a calling device requesting an I/O operation on a data object, such as an HTTP code to be returned. As discussed above, the frontend  162  may obtain such return value and undertake appropriate action, such as returning an error or HTTP code to a calling device, implementing an additional data manipulation, performing an I/O operation on output data, etc. In some instances, a return value may be explicitly specified within code of the task. In other instances, such as where no return value is specified within the code, a default return value may be returned (e.g., a ‘1’ indicating success). The routine  800  then ends at block  814 . 
       FIGS. 9 through 12B  include some, but not all, of the components of  FIG. 1  described above merely for simplicity and the purposes of discussion. However, any reference in the disclosure related to  FIGS. 9 through 12B, 13 , or  14  to a component of  FIG. 1  that is not depicted in any of  FIGS. 9 through 12B  is referring to the corresponding component of  FIG. 1  even though such component may not be explicitly depicted in  FIGS. 9 through 12B . 
       FIG. 9  is another block diagram of the illustrative operating environment  100  in which a staging environment  902  operates to fetch objects for execution by the task code  504  and manage output data produced by execution of the task code  504 . For example, the staging environment  902  can function as an interface between the object storage service  160  and the on-demand code execution system  120 , configured to retrieve input data from the object data store(s)  168  and/or client device(s)  102  for storage in the storage location (e.g., the memory or disk) pointed to by the input file handle  506  and pass output data produced by execution of the task code  504  from the storage location (e.g., the memory or disk) pointed to by the output file handle  508  to the object data store(s)  168  and/or client device(s)  102 . 
     In an embodiment, the frontend  130  of the on-demand code execution system  120  may instruct a worker manager  140  to select or generate a staging VM instance in response to reception of a call from the frontend  162  to execute a task specified within the modifications against the input data specified within the call. Alternatively, the frontend  130  may instruct a worker manager  140  to select or generate the staging VM instance prior to receiving a call, such as when the on-demand code execution system  120  is launched. The staging VM instance illustratively represents the staging environment  902 , and thus the staging environment  902  and the execution environment  502  may be implemented by different VM instances running within the on-demand code execution system  120 . 
     During generation of the staging environment  902 , the on-demand code execution system  120  further provisions the staging environment  902  with a data fetcher  904  and an output data manager  906 . The data fetcher  904  can fetch objects or other input data for storage in the memory or disk pointed to by the input file handle  506  and/or can control the rate at which objects or other input data are fetched. For example, the data fetcher  904  can fetch an object or a portion of an object from a client device  102  via the frontend(s)  162  or from the object data store(s)  168  in response to a PUT operation, and the data fetcher  904  can fetch an object or a portion of an object from the object data store(s)  168  in response to a GET operation. The data fetcher  904  can also fetch an object or a portion of an object produced by another task code  504  separate from the task code  504  for which the data fetcher  904  is fetching input data such that the task code  504  can use as an input the output data produced by another task code  504 . For example, the data fetcher  904  can fetch an object or a portion of an object from the output data manager  906  of the staging environment  902 —which read the object or portion thereof from memory or disk pointed to by the output file handle  508  of a second execution environment  502  separate from the execution environment  502  for which the data fetcher  904  is fetching input data—or from the output data manager  906  of a different staging environment  902  that is separate from the staging environment  902  that includes the data fetcher  904 . Upon fetching an object or a portion thereof, the data fetcher  904  can store the object or the portion of the object in memory or a disk referenced by the input file handle  506 . Thus, the data fetcher  904  can store a fetched object or a portion thereof in a storage location in which the task code  504  has file-level access. 
     In an embodiment, the memory or disk referenced by the input file handle  506  may be memory or disk of the on-demand code execution system  120  that is shared by the staging environment  902  and the execution environment  502  (e.g., by the two VM instances representing the staging environment  902  and the execution environment  502 ). Thus, the data fetcher  904  can write to this shared memory or disk and the execution environment  502  can read from this shared memory or disk. Because the memory or disk is shared, the data fetcher  904  can monitor the memory or disk to determine when the input data stored therein has been read by the execution environment  502 . For example, the fact that the execution environment  502  has read the input data stored in the memory or disk may indicate that the input data has or will be manipulated by execution of the task code  504  and that staging of the input data is no longer necessary. In response to determining that the input data stored on the memory or disk has been read by the execution environment  502 , the data fetcher  904  can replace the input data stored on the memory or disk with new input data if such new input data is to be manipulated by the task code  504  in the future. 
     The data fetcher  904  can fetch an object or a portion thereof by implementing one of several different approaches. For example, the data fetcher  904  can fetch an entire object and store the entire object in the memory or disk pointed to by the input file handle  506 . Once the entire object is stored in the memory or disk, the task code  504  can begin manipulating the entire object to produce output data. Thus, the user-submitted task code  504  can be written to manipulate input data regardless of the location from which the input data originated given that the data fetcher  904  handles the initial fetching, storing the input data in a set location known to the execution environment  502  and task code  504 . 
     As another example, the data fetcher  904  can fetch an object in portions (e.g., blocks, chunks, etc.) rather than all at once (e.g., the data fetcher  904  can stream the object in blocks or chunks) and allow the task code  504  to execute when a first portion of the object is fetched and stored in the memory or disk. Specifically, the data fetcher  904  can fetch a first portion (e.g., a first block, a first chunk, etc.) of an object and store the first portion in the memory or disk pointed to by the input file handle  506 . Once the first portion of the object is stored in the memory or disk, the task code  504  can begin manipulating the first portion of the object by accessing the first portion stored in the memory or disk. Before, during, and/or after the task code  504  begins manipulating the first portion, the data fetcher  904  can begin fetching the second portion of the object for storage in the memory or disk pointed to by the input file handle  506 . The data fetcher  904  may store the fetched second portion in the memory or disk pointed to by the input file handle  506  once the data fetcher  904  determines that the task code  504  has read the first portion stored in the memory or disk pointed to by the input file handle  506 . The data fetcher  904  can repeat these operations until some or all of the blocks or chunks of the object have been fetched for manipulation by the task code  504 . Thus, retrieval of an object and processing of at least a portion of the object can overlap in time. 
     In general, the data fetcher  904  can fetch a portion of an object at a rate that is dependent on an object fetch rate and an object manipulation rate. For example, if the data fetcher  904  fetches objects or portions thereof faster than a time it takes the execution environment  502  to manipulate objects or portions thereof, then the data fetcher  904  may not be able to store fetched objects or portions thereof given that the objects or portions thereof already stored in the memory or disk pointed to by the input file handle  506  may not yet have been read. Conversely, if the data fetcher  904  fetches objects or portions thereof slower than a time it takes the execution environment  502  to manipulate objects or portions thereof, then execution of the task code  504  may be delayed. Thus, the data fetcher  904  can determine a rate at which the task code  504  manipulates a byte (or KB, MB, GB, etc.) of data (e.g., an object manipulation rate) and a rate at which the data fetcher  904  fetches a byte (or KB, MB, GB, etc.) of data (e.g., an object fetch rate). If the object manipulation rate is slower than the object fetch rate, the data fetcher  904  can decrease the object fetch rate to match the object manipulation rate, can delay fetching of a next portion of an object until N % of a previous portion of the object has been manipulated by the task code  504  (e.g., where the rate at which the remaining part of the previous portion of the object (e.g., 100%−N % of the previous portion of the object) can be manipulated by the task code  504  is equivalent to the object fetch rate), can delay fetching of a next portion of an object until the task code  504  has manipulated a previous portion of the object for a certain amount of time (e.g., where the remaining time to complete manipulation of the previous portion of the object is equivalent to the time for fetching the next portion of the object), can fetch a certain amount of a next portion of the object and then stall the fetch until the time to fetch the remaining amount of the next portion of the object is equivalent to the time to complete manipulation of the previous portion of the object, and/or the like. If the object manipulation rate is faster than the object fetch rate, the data fetcher  904  can continue fetching objects or portions thereof as before, can cause execution of the task code  504  to pause until the current fetch is complete, and/or the like. 
     As another example, the data fetcher  904  can fetch objects or portions thereof on-demand. Specifically, the data fetcher  904  can delay fetching an object or a portion thereof until the data fetcher  904  determines what portion(s) of an object are being accessed by the task code  504 . In particular, the data fetcher  904  can monitor data requests sent by the task code  504  to the input file handle  506  to determine what portion(s) of an object are being requested by the task code  504 . Once the portion(s) of the object are determined, the data fetcher  904  can fetch the determined portion(s) from the object data store(s)  168  and/or the client device(s)  102  for storage in the memory or disk pointed to by the input file handle  506 . The data fetcher  904  can fetch all of the determined portion(s) at once and store all of the determined portion(s) in the memory or disk at the same time. Alternatively, the data fetcher  904  can fetch and store the determined portion(s) in sequence. For example, the data fetcher  904  can fetch and store the first determined portion in the memory or disk first, fetch the second determined portion while the first determined portion is being read by the task code  504  and store the second determined portion in the memory or disk after the task code  504  has finished reading the first determined portion, fetch the third determined portion while the second determined portion is being read by the task code  504  and store the third determined portion in the memory or disk after the task code  504  has finished reading the second determined portion, and so on. Fetching objects or portions thereof on-demand may help the data fetcher  904  reduce a load on the object storage service  160  because the data fetcher  904  may only fetch the portion(s) of an object desired by the task code  504  to complete execution rather than the entire object. 
     If the data fetcher  904  is fetching portions of an object rather than an entire object, the data fetcher  904  can divide the object into various blocks or chunks prior to the retrieval. For example, the data fetcher  904  can divide any fetched object into blocks or chunks of a fixed size (e.g., 10 MB, 100 MB, etc.). In other embodiments, a client device  102  may have initiated a multi-part upload in which the object was divided into blocks or chunks for upload. Because the object may have already been divided by the client device  102  or another system, there may be efficiencies in having the data fetcher  904  fetch the already-created blocks or chunks rather than having the data fetcher  904  re-divide the object into a new set of blocks or chunks. Thus, the data fetcher  904  may not perform any division, and may rather fetch the already-created blocks or chunks of the object. 
     The data fetcher  904  can also using a caching technique to reduce the number of fetches. For example, the data fetcher  904  can store the object or portions thereof in the memory or disk pointed to by the input file handle  506 . The data fetcher  904  may allow the fetched object or object portion to remain in the memory or disk even after the task code  504  has read the object or object portion for a set period of time. When the data fetcher  904  is instructed to retrieve an object or object portion for manipulation by the task code  504 , the data fetcher  904  can first check the memory or disk pointed to by the input file handle  506  to determine whether the object or object portion to retrieve is stored therein. If the object or object portion to retrieve is stored therein, then the data fetcher  904  may not perform any fetch operations to fetch the object or object portion (and the task code  504  can read the already retrieved object or object portion from the memory or disk pointed to by the input file handle  506 ). If the object or object portion to retrieve is not stored therein, then the data fetcher  904  can retrieve the object or object portion as described herein. The data fetcher  904  can optionally store object or object portion identifiers (e.g., object or object portion names, object or object portion signatures, etc.) of objects or object portions currently stored in the memory or disk pointed to by the input file handle  506 , and use the stored identifiers to determine whether an object or object portion to retrieve has an identifier that matches one of the stored identifiers. In fact, the data fetcher  904  can proactively retrieve objects or object portions in anticipation of the objects or object portions being needed later by the task code  504 . For example, if the data fetcher  904  determines that a first byte of an object should be retrieved, the data fetcher  904  may nonetheless retrieve the first byte of the object and one or more additional bytes of the object (since retrieving multiple bytes of the object may not take much longer than just retrieving one byte of the object). In the future, the data fetcher  904  can then determine whether a byte to retrieve has already been retrieved and stored in the memory or disk pointed to by the input file handle  506 . 
     After the task code  504  has finished manipulating the input data to produce output data, the task code  504  can write the output data to memory or disk pointed to by the output file handle  508 . Like the memory or disk pointed to by the input file handle  506 , the memory or disk pointed to by the output file handle  508  may be shared by the staging environment  902  and the execution environment  502 . Thus, the output data manager  906  can monitor the memory or disk pointed to by the output file handle  508  to determine whether any output data is written thereto. Once output data is written to the memory or disk pointed to by the output file handle  508 , the output data manager  906  can retrieve the output data from the memory or disk and forward the output data to the frontend(s)  162  for storage in the object data store(s)  168  (e.g., if a PUT operation) or for transmission to a client device  102  (e.g., if a GET operation). The output data manager  906  can also forward the output data to the data fetcher  904  for storage in the memory or disk that another task code  504  reads, such that the other task code  504  can use the output data as an input and generate a corresponding output using the output data. For example, the output data manager  906  can forward the output data to the data fetcher  904 —which then stores the output data in memory or disk pointed to by the input file handle  906  of a second execution environment  502  separate from the execution environment  502  from which produced the output data—or to another data fetcher  904  in a second staging environment  902  separate from the staging environment  902  that includes the output data manager  906 . 
     The task code  504  can generate a single object as the output data or can generate a stream of output data. For example, if the task code  504  reads an entire object from the memory or disk pointed to by the input file handle  506  as input data, then the task code  504  can generate a single object (e.g., a manipulated version of the entire object) as the output data. Alternatively, if the task code  504  reads an entire object from the memory or disk pointed to by the input file handle  506  as input data, the task code  504  can process the entire object in parts and generate a stream of output data as a result. As another example, if the task code  504  reads a stream of objects or portions thereof from the memory or disk pointed to by the input file handle  506  as input data, then the task code  504  can process each object or portion thereof in sequence and therefore produce a stream of output data. In some embodiments, each instance of output data in the stream corresponds to a manipulated version of an object or a portion thereof received as input data. In other embodiments, each instance of output data in the stream does not correspond directly to a manipulated instance of an object or portion thereof in the input stream. Rather, an instance of output data in the stream may correspond to a manipulated portion of an instance of an object or portion thereof in the input stream, may correspond to multiple manipulated instances of an object or portion thereof in the input stream, may correspond to a single manipulated instance of an object or portion thereof in the input stream, and/or any combination thereof. In other words, the manner in which the input stream is broken into chunks or blocks may be the same or different than the manner in which the output stream is broken into chunks or blocks (e.g., the input stream is broken into 1 MB chunks, and the output stream is broken into 600 KB chunks or broken into 10 MB chunks). Alternatively, if the task code  504  reads a stream of objects or portions thereof from the memory or disk pointed to by the input file handle  506  as input data, the task code  504  can combine the results of manipulating some or all of the individual object or portion thereof to form a single instance of output data. 
     If the task code  504  generates a stream of output data, the task code  504  can write the next portion of the stream to the memory or disk pointed to by the output file handle  508  to replace a previous portion of the stream after the previous portion of the stream is read and/or deleted by the output data manager  906  (e.g., the task code  504  can monitor the memory or disk pointed to by the output file handle  508  to determine when output data is read and/or deleted). Alternatively, the task code  504  can write multiple portions of the stream to different portions of the memory or disk pointed to by the output file handle  508  such that portions of the stream already written to the memory or disk do not necessarily have to be overwritten. This may be useful in circumstances in which a client device  102  is attempting to retrieve the output data, but is reading the output data in blocks, chunks, or specific byte ranges and is making multiple, parallel fetches to the service provider system  110 , or in situations in which there are network issues and the client device  102  retries one or more times to retrieve the output data. 
     The output data manager  906  may be further configured to determine when output data stored in the memory or disk pointed to by the output file handle  506  can be deleted. In an embodiment, because a client device  102  can make one or more parallel fetches to obtain output data or can attempt to retrieve the output data one or more times if there are network issues, the output data manager  906  may not delete output data stored on the memory or disk immediately after the output data is first read or after the task code  504  generates a new piece of output data. Rather, the output data manager  906  can maintain a copy of the output data on the memory or disk for a set period of time, until all portions of the output data have been transmitted to the client device  102  at least a threshold number of times to account for network issues (e.g., 1, 2, 3, 4, 5, etc.), until the memory or disk is full and additional space is needed to store future output data generated by the task code  504  (where the output data manager  906  can delete the least-recently accessed output data first, the oldest output data first, etc.), and/or the like. 
     As described herein, input data being streamed to the memory or disk pointed to by the input file handle  506  does not necessarily mean the task code  504  will generate a stream of output data, and an entire object being written to the memory or disk pointed to by the input file handle  506  does not necessarily mean that the task code  504  will generate a single instance of output data. Rather, regardless of the approach taken by the data fetcher  904  to fetch an object or a portion thereof, the task code  504  can generate a single instance of output data or a stream of output data. As an illustrative example, the data fetcher  904  can fetch a stream of object portions so that the task code  504  can compress each individual object portion and produce a stream of compressed output data, where each individual item in the stream is a compressed object portion. Thus, the data fetcher  904  can stream input data to the execution environment  502  and the execution environment  502  can produce a stream of output data in this example. 
     As another illustrative example, the data fetcher  904  can fetch an entire object, such as a Parquet object, that includes rows and columns. Once the entire object is written to the memory or disk pointed to by the input file handle  506 , the task code  504  can manipulate data in each row of the object, producing a stream of output data in which each individual item in the stream is a manipulated version of the data in a specific row. Thus, the data fetcher  904  can fetch an entire object and the execution environment  502  can produce a stream of output data in this example. 
     As another illustrative example, the data fetcher  904  can identify a portion of an object that is being requested by the task code  504  (e.g., a column in a Parquet object), and retrieve just this portion of the object as a result. Once the object portion is written to the memory or disk pointed to by the input file handle  506 , the task code  504  can manipulate data in each row of the column, producing a stream of output data in which each individual item in the stream is a manipulated version of the data in a specific row. Thus, the data fetcher  904  can fetch input data on-demand and the execution environment  502  can produce a stream of output data in this example. 
     As another illustrative example, the data fetcher  904  can fetch a stream of object portions so that the task code  504  can generate a fingerprint for object portion. Once the task code  504  has generated the individual fingerprints, the task code  504  can combine the individual fingerprints to form a single fingerprint. The single fingerprint may be the output data pass to a client device  102  so that the client device  102  can compare the single fingerprint to a known fingerprint to validate whether the object was stored properly. Thus, the data fetcher  904  can stream input data to the execution environment  502  and the execution environment  502  can produce a single instance of output data in this example. 
     Not only can any combination of object fetching approach and output data generation be implemented, but the data fetcher  904  can also blend different object fetching approaches during the same fetch (e.g., perform an on-demand and stream fetch, perform an on-demand and entire object fetch, perform a stream fetch and an entire object fetch, etc.). For example, the data fetcher  904  can identify a portion of an object that is being requested by the task code  504 . Once identified, the data fetcher  904  can retrieve just this portion of the object and stream this portion of the object as input data for storage in the memory or disk pointed to by the input file handle  506 . As an illustrative example, the task code  504  may be attempting to manipulate the data in one column of a Parquet object. Once the data fetcher  904  identifies the column that the task code  504  is trying to access, the data fetcher  904  can retrieve just this column from the Parquet object, and stream the column of the Parquet object to the memory or disk pointed to by the input file handle  506  on a row-by-row basis. Thus, the data fetcher  904  can fetch data of the first row of the column of the Parquet object and store the data of the first row in the memory or disk. The data fetcher  904  can then fetch the data of the second row of the column of the Parquet object and store the data of the second row in the memory or disk once the task code  504  has read the data of the first row. The data fetcher  904  can then fetch the data of the third row of the column, and so on. 
     In further embodiments, the on-demand code execution system  120  can include one or more double buffers that are shared by the staging environment  902  and the execution environment  502 . For example, one double buffer may store input data being fetched by the data fetcher  904  and another double buffer may store input data being processed by the task code  504 . In particular, the data fetcher  904  may initially write input data to a first double buffer. Once the first double buffer is filled or the task code  504  is ready to begin processing input data, the data fetcher  904  can begin writing additional input data to a second double buffer, and the input file handle  506  may begin pointing to the first double buffer (in response to an operation performed by the data fetcher  904  or the on-demand execution system  120 ) so that the task code  504  can begin processing the input data stored in the first double buffer. While the task code  504  is processing the input data stored in the first double buffer, the data fetcher  904  can fetch objects or portions thereof and store such objects or object portions in the second double buffer. Once the task code  504  has finished processing the input data stored in the first double buffer, the data fetcher  904  or the on-demand code execution system  120  can cause the input file handle  506  to point to the second double buffer so that the task code  504  can continue the processing by processing the input data stored in the second double buffer. The data fetcher  904  can then delete or overwrite the input data stored in the first double buffer with new input data that has been fetched by the data fetcher  904  while the task code  504  processes the input data stored in the second double buffer. This process can repeat until some or all of the input data has been processed by the task code  504 . 
     In further embodiments, the on-demand code execution system  120  can include one or more circular buffers that are shared by the staging environment  902  and the execution environment  502 . The circular buffer can be pointed to by the input file handle  506 . The circular buffer can include a read pointer used by the task code  504  and a write pointer used by the data fetcher  904 . For example, the data fetcher  904  can store a fetched object or object portion at a location of the write pointer and move the write pointer to the end of the newly stored object or object portion. The data fetcher  904  can repeat this operation for each newly fetched object or object portion. Once the data fetcher  904  has written to the end of the circular buffer, the data fetcher  904  can begin writing to the beginning of the circular buffer. Similarly, the task code  504  can read input data located at a location of the read pointer, and can move the read pointer to the end of the read object or object portion once the object or object portion is read. The task code  504  can repeat this operation for each new piece of input data to be processed. Once the task code  504  has read the object or object portion stored in the last position of the circular buffer, the task code  504  can begin reading input data from the first position of the circular buffer. In general, the data fetcher  904  can monitor the read and/or write pointers to ensure that the write pointer does not overtake the read pointer, which could otherwise result in the data fetcher  904  overwriting input data that has not yet been read by the task code  504 . 
     In further embodiments, objects (or portions thereof) stored in the object data store(s)  168  or provided by a client device  102  can be encrypted using a user-defined encryption key or encryption algorithm. The data fetcher  904  can retrieve encrypted objects or portions thereof and the user-defined encryption key so that the data fetcher  904  can decrypt the encrypted objects or portions thereof using the user-defined encryption key. However, to preserve user privacy and ensure that the objects or portions thereof do not become compromised, the data fetcher  904  can re-encrypt the decrypted objects using a temporary encryption key separate from the user-defined encryption key, and provide the temporary encryption key to the execution environment  502 . Thus, the object or portions thereof can be stored in the memory or disk pointed to by the input file handle  506  in an encrypted state to provide added protection. The execution environment  502  (e.g., the task code  504 ) can then read the encrypted object or portions thereof from the memory or disk, decrypt the encrypted object or portions thereof using the temporary encryption key, manipulate the decrypted object or portion thereof, encrypt the manipulated object or portion thereof using the temporary encryption key (or a second temporary encryption key), and store the encrypted manipulated object or portion thereof in the memory or disk pointed to by the output file handle  508 . The output data manager  906  can then read the encrypted manipulated object or portion thereof from the memory or disk pointed to by the output file handle  508 , decrypt the encrypted manipulated object or portion thereof using the temporary encryption key (or the second temporary encryption key as provided by the execution environment  502 ) (and optionally destroy the temporary or second temporary encryption key so that any data remaining in the input or output staging areas is no longer readable to a malicious user that may be trying to access the data), encrypt the decrypted manipulated object or portion thereof using the user-defined encryption key, and then forward the encrypted manipulated object or portion thereof for transmission to the client device  102  or storage in the object data store(s)  168 . Thus, the user-defined encryption key is never provided to the execution environment  502 —which can be a less secure area given that the execution environment  502  can be created or invoked by a user that does not have access to the user-defined encryption key, and therefore the user-defined encryption key is less likely to become compromised—yet the underlying data can remain encrypted in the input and output staging areas and be manipulated by the task code  504 . 
       FIG. 10  is a block diagram of the illustrative operating environment  100  illustrating the operations performed by the components of the operating environment  100  to fetch an entire object and produce a single instance of output data as a result, according to one embodiment. The block diagram of  FIG. 10  begins after a GET or PUT operation has already been received by the frontend(s)  162 . As illustrated in  FIG. 10 , the data fetcher  904  can fetch entire input data from the frontend(s)  162  (e.g., in response to a PUT operation) at ( 1 A) or can fetch an entire object from the object data store(s)  168  (e.g., in response to a GET operation) at ( 1 B). 
     The data fetcher  904  can then store the input data or object in memory or disk pointed to by the input file handle  506  at ( 2 ). In this embodiment, the entire input data or object may have a size that is less than the available capacity of the memory or disk pointed to by the input file handle  506 . The task code  504  can then retrieve the input data or object from the memory or disk pointed to by the input file handle  506  at ( 3 ). 
     The task code  504  can execute using the read input data or object to produce output data at ( 4 ). For example, the task code  504  can execute to manipulate the input data or object. The produced output data may be a single instance of output data. Once produced, the task code  504  can store the output data in memory or disk pointed to by the output file handle  508  at ( 5 ). 
     The output data manager  906  can monitor the memory or disk pointed to by the output file handle  508  given that the memory or disk may be shared by the execution environment  502  and the staging environment  902 . Thus, once the output data manager  906  has detected that output data has been written to the memory or disk pointed to by the output file handle  508 , the output data manager  906  can retrieve the output data at ( 6 ) and transmit the output data to the frontend(s)  162  at ( 7 ). If a PUT operation had been received, then the frontend(s)  162  may store the output data in the object data store(s)  168  at ( 8 ). Otherwise, if a GET operation had been received, then the frontend(s)  162  may forward the output data to a client device  102 . 
       FIGS. 11A-11B  are block diagrams of the illustrative operating environment  100  illustrating the operations performed by the components of the operating environment  100  to fetch a stream of input data and to produce a stream of output data, according to one embodiment. The block diagram of  FIGS. 11A-11B  begin after a GET or PUT operation has already been received by the frontend(s)  162 . As illustrated in  FIG. 11A , the data fetcher  904  can fetch a first portion of input data from the frontend(s)  162  (e.g., in response to a PUT operation) at ( 1 A) or can fetch a first portion of an object from the object data store(s)  168  (e.g., in response to a GET operation) at ( 1 B). 
     The data fetcher  904  can then store the first portion of the input data or object in memory or disk pointed to by the input file handle  506  at ( 2 ). The task code  504  can then retrieve the first portion of the input data or object from the memory or disk pointed to by the input file handle  506  at ( 3 ). 
     The data fetcher  904  can determine at ( 4 ) that the first portion of the input data or object has been read by the task code  504 . For example, because the memory or disk pointed to by the input file handle  506  may be shared by the staging environment  902  and the execution environment  502 , the data fetcher  904  can monitor the shared memory or disk to determine when the first portion of the input data or object has been read and is no longer needed. In response to determining that the first portion of the input data or object is read, the data fetcher  904  can fetch a next portion of input data from the frontend(s)  162  (e.g., in response to a PUT operation) at ( 5 A) or can fetch a next portion of an object from the object data store(s)  168  (e.g., in response to a GET operation) at ( 5 B). 
     Before, during, and/or after the data fetcher  904  fetches the next portion of the input data or object, the task code  504  can execute using the read first portion of the input data or object to produce output data at ( 6 ). For example, the task code  504  can execute to manipulate the first portion of the input data or object. The produced output data may be a first instance in a stream of output data. 
     Before, during, and/or after the task code  504  executes, the data fetcher  904  can store the next portion of the input data or object in the memory or disk pointed to by the input file handle  506  at ( 7 ). The data fetcher  904  can delete or overwrite the first portion of the input data or object with the next portion of the input data or object. Alternatively, the data fetcher  904  can write the next portion of the input data or object to a different location than the first portion of the input data or object, such as if a double buffer or circular buffer is used. 
     As illustrated in  FIG. 11B , the task code  504  can store the output data in memory or disk pointed to by the output file handle  508  at ( 8 ). After the task code  504  writes the output data to the memory or disk, the task code  504  can retrieve the next portion of the input data or object stored in the memory or disk pointed to by the input file handle  506  at ( 9 ). 
     The output data manager  906  can monitor the memory or disk pointed to by the output file handle  508  given that the memory or disk may be shared by the execution environment  502  and the staging environment  902 . Thus, once the output data manager  906  has detected that output data has been written to the memory or disk pointed to by the output file handle  508 , the output data manager  906  can retrieve the output data at ( 10 ) and transmit the output data to the frontend(s)  162  at ( 11 ). If a PUT operation had been received, then the frontend(s)  162  may store the output data in the object data store(s)  168  at ( 12 ). Otherwise, if a GET operation had been received, then the frontend(s)  162  may forward the output data to a client device  102 . 
     Before, during, and/or after the output data is transmitted to the frontend(s)  162  for storage in the object data store(s)  168  or transmission to a client device  102 , the task code  504  can execute using the next portion of the input data or object to produce next output data at ( 13 ). For example, the task code  504  can execute to manipulate the next portion of the input data or object. The produced next output data may be a second instance in a stream of output data. 
     The task code  504  can store the next output data in memory or disk pointed to by the output file handle  508  at ( 14 ). Once the output data manager  906  has detected that next output data has been written to the memory or disk pointed to by the output file handle  508 , the output data manager  906  can retrieve the next output data at ( 15 ) and transmit the next output data to the frontend(s)  162  at ( 16 ). If a PUT operation had been received, then the frontend(s)  162  may store the next output data in the object data store(s)  168  at ( 17 ). Otherwise, if a GET operation had been received, then the frontend(s)  162  may forward the next output data to a client device  102 . 
       FIGS. 12A-12B  are block diagrams of the illustrative operating environment  100  illustrating the operations performed by the components of the operating environment  100  to fetch input data on-demand to produce a single instance of output data, according to one embodiment. The block diagram of  FIGS. 12A-12B  begin after a GET or PUT operation has already been received by the frontend(s)  162 . As illustrated in  FIG. 12A , the data fetcher  904  does not immediately begin fetching input data or an object. Rather, the task code  504  begins execution at ( 1 ). The data fetcher  904  can monitor the requests submitted by the task code  504  as a result of the execution, and can determine that the task code  504  is attempting to access a first portion of an input data or object at ( 2 ) in response to the monitoring. Thus, the data fetcher  904  can fetch the first portion of input data from the frontend(s)  162  (e.g., in response to a PUT operation) at ( 3 A) or can fetch the first portion of an object from the object data store(s)  168  (e.g., in response to a GET operation) at ( 3 B). 
     The data fetcher  904  can then store the first portion of the input data or object in memory or disk pointed to by the input file handle  506  at ( 4 ). The task code  504  can then retrieve the first portion of the input data or object from the memory or disk pointed to by the input file handle  506  at ( 5 ). 
     The task code  504  can then complete execution using the first portion of the input data or object to produce output data at ( 6 ). In this way, the data fetcher  904  does not need to retrieve the entire input data or object in order for the task code  504  to complete the desired data manipulation. 
     As illustrated in  FIG. 12B , the task code  504  can store the output data in memory or disk pointed to by the output file handle  508  at ( 7 ). Once the output data manager  906  has detected that output data has been written to the memory or disk pointed to by the output file handle  508 , the output data manager  906  can retrieve the output data at ( 8 ) and transmit the output data to the frontend(s)  162  at ( 9 ). If a PUT operation had been received, then the frontend(s)  162  may store the output data in the object data store(s)  168  at ( 10 ). Otherwise, if a GET operation had been received, then the frontend(s)  162  may forward the output data to a client device  102 . 
       FIG. 13  is a flow chart depicting an illustrative routine for processing a streamed object on the on-demand code execution system  120  of  FIG. 1 . The routine  1300  is illustratively implemented by the on-demand code execution system  120  of  FIG. 1 . For example, the routine  1300  can be implemented by the staging environment  902  of  FIG. 9 . 
     At block  1302 , a first portion of input data or an object is fetched and stored in an input staging location. For example, the input staging location may be the memory or disk pointed to by the input file handle  506 . 
     At block  1304 , a determination is made that the first portion of the input data or object has been read from the input staging location. For example, the input staging location may be shared between the staging environment  902  and the execution environment  904 . Thus, the data fetcher  904  can monitor the input staging location to determine when the task code  504  reads the first portion stored therein. Once read, this may indicate that the first portion is no longer needed and other input data or objects can be stored therein. 
     At block  1306 , a determination is made as to whether more portions of the input data or object are available (e.g., whether additional portions of the input data or object have yet to be fetched) and/or need to be processed. If additional portions of the input data or object are available and/or need to be processed, then the routine  1300  proceeds to block  1308  so that at least one additional portion of the input data or object can be fetched and stored. Otherwise, if the additional portions of the input data or object are unavailable and/or do not need to be processed, then the routine  1300  ends, as shown at block  1312 . 
     At block  1308 , the next portion of the input data or object is fetched and stored in the input staging location. For example, the data fetcher  904  can delete the first portion of the input data or object and store the next portion of the input data or object in place of the first portion. 
     At block  1310 , a determination is made that the next portion of the input data or object has been read from the input staging location. Once read, this may indicate that the next portion is no longer needed and other input data or objects can be stored therein. Accordingly, the routine  1300  can proceed back to block  1306  to determine whether additional portions of the input data or object should be fetched. 
       FIG. 14  is a flow chart depicting an illustrative routine for processing an object fetched on-demand on the on-demand code execution system  120  of  FIG. 1 . The routine  1400  is illustratively implemented by the on-demand code execution system  120  of  FIG. 1 . For example, the routine  1400  can be implemented by the staging environment  902  of  FIG. 9 . 
     At block  1402 , a determination is made that the task code is attempting to access a first portion of input data or an object. For example, the data fetcher  904  can monitor the read commands submitted by the task code  504 . The task code  504  may submit a read command for at least a portion of an object on which a data manipulation will occur. 
     At block  1404 , the first portion of the input data or object is fetched. The first portion of the input data or object may be fetched instead of the entire input data or object. If a determination is made that the task code is attempting to access additional portions of the input data or object as well, then the additional portions of the input data or object can be fetched with the first portion or fetched separately, either all at once, in sequence (e.g., as a stream of input data), or any combination thereof. 
     At block  1406 , the first portion of the input data or object is stored in an input staging location. For example, the input staging location may be the memory or disk pointed to by the input file handle  506 . 
     At block  1408 , output data stored in an output staging location and produced as a result of the task code being executed on the first portion of the input data or object is retrieved. For example, the output staging location may be the memory or disk pointed to by the output file handle  508 . The output data manager  906  can monitor the output staging location to determine when output data is written thereto. 
     At block  1410 , the output data is transmitted for transmission to a client device or storage in an object data store. For example, the output data can be transmitted to the frontend(s)  162 . Once the output data is transmitted, the routine  1400  ends, as shown at block  1412 . 
     All of the methods and processes described above may be embodied in, and fully automated via, software code modules executed by one or more computers or processors. The code modules may be stored in any type of non-transitory computer-readable medium or other computer storage device. Some or all of the methods may alternatively be embodied in specialized computer hardware. 
     Conditional language such as, among others, “can,” “could,” “might” or “may,” unless specifically stated otherwise, are otherwise understood within the context as used in general to present that certain embodiments include, while other embodiments do not include, certain features, elements or steps. Thus, such conditional language is not generally intended to imply that features, elements or steps are in any way required for one or more embodiments or that one or more embodiments necessarily include logic for deciding, with or without user input or prompting, whether these features, elements or steps are included or are to be performed in any particular embodiment. 
     Disjunctive language such as the phrase “at least one of X, Y or Z,” unless specifically stated otherwise, is otherwise understood with the context as used in general to present that an item, term, etc., may be either X, Y or Z, or any combination thereof (e.g., X, Y or Z). Thus, such disjunctive language is not generally intended to, and should not, imply that certain embodiments require at least one of X, at least one of Y or at least one of Z to each be present. 
     Unless otherwise explicitly stated, articles such as ‘a’ or ‘an’ should generally be interpreted to include one or more described items. Accordingly, phrases such as “a device configured to” are intended to include one or more recited devices. Such one or more recited devices can also be collectively configured to carry out the stated recitations. For example, “a processor configured to carry out recitations A, B and C” can include a first processor configured to carry out recitation A working in conjunction with a second processor configured to carry out recitations B and C. 
     The term “or” should generally be understood to be inclusive, rather than exclusive. Accordingly, a set containing “a, b, or c” should be construed to encompass a set including a combination of a, b, and c. 
     Any routine descriptions, elements or blocks in the flow diagrams described herein or depicted in the attached figures should be understood as potentially representing modules, segments, or portions of code which include one or more executable instructions for implementing specific logical functions or elements in the routine. Alternate implementations are included within the scope of the embodiments described herein in which elements or functions may be deleted, or executed out of order from that shown or discussed, including substantially synchronously or in reverse order, depending on the functionality involved as would be understood by those skilled in the art. 
     It should be emphasized that many variations and modifications may be made to the above-described embodiments, the elements of which are to be understood as being among other acceptable examples. All such modifications and variations are intended to be included herein within the scope of this disclosure and protected by the following claims.