Patent ID: 12204436

DETAILED DESCRIPTION

In the following description, for the purposes of explanation and to provide a thorough understanding, numerous specific details are set forth. One or more embodiments may be practiced without these specific details. Features described in one embodiment may be combined with features described in a different embodiment. In some examples, well-known structures and devices are described with reference to a block diagram form, in order to avoid unnecessarily obscuring the present invention.

The following table of contents is provided for reference purposes only and should not be construed as limiting the scope of one or more embodiments.1. GENERAL OVERVIEW2. ARCHITECTURAL OVERVIEW2.1. EXAMPLE ARCHITECTURE2.2. EXAMPLE CLASS FILE STRUCTURE2.3. EXAMPLE VIRTUAL MACHINE ARCHITECTURE2.4. LOADING, LINKING, AND INITIALIZING3. EXAMPLE RUNTIME STACK4. INCREMENTAL STACK WALKING5. STACK UNWINDING6. PERFORMANCE COMPARISON7. COMPUTER NETWORKS AND CLOUD NETWORKS8. HARDWARE OVERVIEW9. MISCELLANEOUS; EXTENSIONS

1. General Overview

One or more embodiments leverage the observation that except for the most current frame, most frames are effectively immutable. Most of a program's runtime behavior exercises only a smaller portion of its static call graph, and the exercised parts are frequently revisited during the program's lifetime. Consequently, stack walking tends to involve redundant work, i.e., often discovering the same calling contexts again and again. Such redundant work is well-suited for caching.

To improve stack walking performance, one or more embodiments cache prior results and install one or more marker frames delineating where frames have already been processed. Thus, while the initial stack walk has a cost of O(n), a subsequent stack walk has a cost of O(d)+O(1), where d is the number of new frames installed since the previous stack walk and O(1) is the fixed cost to retrieve the cached results. This approach is referred to herein as “incremental stack walking,” because subsequent stack walks may be performed incrementally without traversing the entire stack. Thus, in addition to improving stack walking performance generally, incremental stack walking supports deeper stack traces, because the costs associated with stack walking are amortized over time.

One or more embodiments described in this Specification and/or recited in the claims may not be included in this General Overview section.

2. Architectural Overview

2.1. Example Architecture

FIG.1illustrates an example architecture in which techniques described herein may be practiced. Software and/or hardware components described with relation to the example architecture may be omitted or associated with a different set of functionality than described herein. Software and/or hardware components, not described herein, may be used within an environment in accordance with one or more embodiments. Accordingly, the example environment should not be constructed as limiting the scope of any of the claims.

As illustrated inFIG.1, a computing architecture100includes source code files101which are compiled by a compiler102into class files103representing the program to be executed. The class files103are then loaded and executed by an execution platform112, which includes a runtime environment113, an operating system111, and one or more application programming interfaces (APIs)110that enable communication between the runtime environment113and the operating system111. The runtime environment113includes a virtual machine104comprising various components, such as a memory manager105(which may include a garbage collector), a class file verifier106to check the validity of class files103, a class loader107to locate and build in-memory representations of classes, an interpreter108for executing the virtual machine104code, and a just-in-time (JIT) compiler109for producing optimized machine-level code.

In an embodiment, the computing architecture100includes source code files101that contain code that has been written in a particular programming language, such as Java, C, C++, C #, Ruby, Perl, and so forth. Thus, the source code files101adhere to a particular set of syntactic and/or semantic rules for the associated language. For example, code written in Java adheres to the Java Language Specification. However, since specifications are updated and revised over time, the source code files101may be associated with a version number indicating the revision of the specification to which the source code files101adhere. The exact programming language used to write the source code files101is generally not critical.

In various embodiments, the compiler102converts the source code, which is written according to a specification directed to the convenience of the programmer, to either machine or object code, which is executable directly by the particular machine environment, or an intermediate representation (“virtual machine code/instructions”), such as bytecode, which is executable by a virtual machine104that is capable of running on top of a variety of particular machine environments. The virtual machine instructions are executable by the virtual machine104in a more direct and efficient manner than the source code. Converting source code to virtual machine instructions includes mapping source code functionality from the language to virtual machine functionality that utilizes underlying resources, such as data structures. Often, functionality that is presented in simple terms via source code by the programmer is converted into more complex steps that map more directly to the instruction set supported by the underlying hardware on which the virtual machine104resides.

In general, programs are executed either as a compiled or an interpreted program. When a program is compiled, the code is transformed globally from a first language to a second language before execution. Since the work of transforming the code is performed ahead of time; compiled code tends to have excellent run-time performance. In addition, since the transformation occurs globally before execution, the code can be analyzed and optimized using techniques such as constant folding, dead code elimination, inlining, and so forth. However, depending on the program being executed, the startup time can be significant. In addition, inserting new code would require the program to be taken offline, re-compiled, and re-executed. For many dynamic languages (such as Java) which are designed to allow code to be inserted during the program's execution, a purely compiled approach may be inappropriate. When a program is interpreted, the code of the program is read line-by-line and converted to machine-level instructions while the program is executing. As a result, the program has a short startup time (can begin executing almost immediately), but the run-time performance is diminished by performing the transformation on the fly. Furthermore, since each instruction is analyzed individually, many optimizations that rely on a more global analysis of the program cannot be performed.

In some embodiments, the virtual machine104includes an interpreter108and a JIT compiler109(or a component implementing aspects of both), and executes programs using a combination of interpreted and compiled techniques. For example, the virtual machine104may initially begin by interpreting the virtual machine instructions representing the program via the interpreter108while tracking statistics related to program behavior, such as how often different sections or blocks of code are executed by the virtual machine104. Once a block of code surpasses a threshold (is “hot”), the virtual machine104invokes the JIT compiler109to perform an analysis of the block and generate optimized machine-level instructions which replaces the “hot” block of code for future executions. Since programs tend to spend most time executing a small portion of overall code, compiling just the “hot” portions of the program can provide similar performance to fully compiled code, but without the start-up penalty. Furthermore, although the optimization analysis is constrained to the “hot” block being replaced, there still exists far greater optimization potential than converting each instruction individually. There are a number of variations on the above described example, such as tiered compiling.

In order to provide clear examples, the source code files101have been illustrated as the “top level” representation of the program to be executed by the execution platform112. Although the computing architecture100depicts the source code files101as a “top level” program representation, in other embodiments the source code files101may be an intermediate representation received via a “higher level” compiler that processed code files in a different language into the language of the source code files101. Some examples in the following disclosure assume that the source code files101adhere to a class-based object-oriented programming language. However, this is not a requirement to utilizing the features described herein.

In an embodiment, compiler102receives as input the source code files101and converts the source code files101into class files103that are in a format expected by the virtual machine104. For example, in the context of the JVM, the Java Virtual Machine Specification defines a particular class file format to which the class files103are expected to adhere. In some embodiments, the class files103contain the virtual machine instructions that have been converted from the source code files101. However, in other embodiments, the class files103may contain other structures as well, such as tables identifying constant values and/or metadata related to various structures (classes, fields, methods, and so forth).

The following discussion assumes that each of the class files103represents a respective “class” defined in the source code files101(or dynamically generated by the compiler102/virtual machine104). However, the aforementioned assumption is not a strict requirement and will depend on the implementation of the virtual machine104. Thus, the techniques described herein may still be performed regardless of the exact format of the class files103. In some embodiments, the class files103are divided into one or more “libraries” or “packages”, each of which includes a collection of classes that provide related functionality. For example, a library may contain one or more class files that implement input/output (I/O) operations, mathematics tools, cryptographic techniques, graphics utilities, and so forth. Further, some classes (or fields/methods within those classes) may include access restrictions that limit their use to within a particular class/library/package or to classes with appropriate permissions.

2.2. Example Class File Structure

FIG.2illustrates an example structure for a class file200in block diagram form according to an embodiment. In order to provide clear examples, the remainder of the disclosure assumes that the class files103of the computing architecture100adhere to the structure of the example class file200described in this section. However, in a practical environment, the structure of the class file200will be dependent on the implementation of the virtual machine104. Further, one or more features discussed herein may modify the structure of the class file200to, for example, add additional structure types. Therefore, the exact structure of the class file200is not critical to the techniques described herein. For the purposes of Section 2.1, “the class” or “the present class” refers to the class represented by the class file200.

InFIG.2, the class file200includes a constant table201, field structures208, class metadata207, and method structures209. In an embodiment, the constant table201is a data structure which, among other functions, acts as a symbol table for the class. For example, the constant table201may store data related to the various identifiers used in the source code files101such as type, scope, contents, and/or location. The constant table201has entries for value structures202(representing constant values of type int, long, double, float, byte, string, and so forth), class information structures203, name and type information structures204, field reference structures205, and method reference structures206derived from the source code files101by the compiler102. In an embodiment, the constant table201is implemented as an array that maps an index i to structure j. However, the exact implementation of the constant table201is not critical.

In some embodiments, the entries of the constant table201include structures which index other constant table201entries. For example, an entry for one of the value structures202representing a string may hold a tag identifying its “type” as string and an index to one or more other value structures202of the constant table201storing char, byte or int values representing the ASCII characters of the string.

In an embodiment, field reference structures205of the constant table201hold an index into the constant table201to one of the class information structures203representing the class defining the field and an index into the constant table201to one of the name and type information structures204that provides the name and descriptor of the field. Method reference structures206of the constant table201hold an index into the constant table201to one of the class information structures203representing the class defining the method and an index into the constant table201to one of the name and type information structures204that provides the name and descriptor for the method. The class information structures203hold an index into the constant table201to one of the value structures202holding the name of the associated class.

The name and type information structures204hold an index into the constant table201to one of the value structures202storing the name of the field/method and an index into the constant table201to one of the value structures202storing the descriptor.

In an embodiment, class metadata207includes metadata for the class, such as version number(s), number of entries in the constant pool, number of fields, number of methods, access flags (whether the class is public, private, final, abstract, etc.), an index to one of the class information structures203of the constant table201that identifies the present class, an index to one of the class information structures203of the constant table201that identifies the superclass (if any), and so forth.

In an embodiment, the field structures208represent a set of structures that identifies the various fields of the class. The field structures208store, for each field of the class, accessor flags for the field (whether the field is static, public, private, final, etc.), an index into the constant table201to one of the value structures202that holds the name of the field, and an index into the constant table201to one of the value structures202that holds a descriptor of the field.

In an embodiment, the method structures209represent a set of structures that identifies the various methods of the class. The method structures209store, for each method of the class, accessor flags for the method (e.g. whether the method is static, public, private, synchronized, etc.), an index into the constant table201to one of the value structures202that holds the name of the method, an index into the constant table201to one of the value structures202that holds the descriptor of the method, and the virtual machine instructions that correspond to the body of the method as defined in the source code files101.

In an embodiment, a descriptor represents a type of a field or method. For example, the descriptor may be implemented as a string adhering to a particular syntax. While the exact syntax is not critical, a few examples are described below.

In an example where the descriptor represents a type of the field, the descriptor identifies the type of data held by the field. In an embodiment, a field can hold a basic type, an object, or an array. When a field holds a basic type, the descriptor is a string that identifies the basic type (e.g., “B”=byte, “C”=char, “D”=double, “F”=float, “I”=int, “J”=long int, etc.). When a field holds an object, the descriptor is a string that identifies the class name of the object (e.g. “L ClassName”). “L” in this case indicates a reference, thus “L ClassName” represents a reference to an object of class ClassName. When the field is an array, the descriptor identifies the type held by the array. For example, “[B” indicates an array of bytes, with “[” indicating an array and “B” indicating that the array holds the basic type of byte. However, since arrays can be nested, the descriptor for an array may also indicate the nesting. For example, “[[L ClassName” indicates an array where each index holds an array that holds objects of class ClassName. In some embodiments, the ClassName is fully qualified and includes the simple name of the class, as well as the pathname of the class. For example, the ClassName may indicate where the file is stored in the package, library, or file system hosting the class file200.

In the case of a method, the descriptor identifies the parameters of the method and the return type of the method. For example, a method descriptor may follow the general form “({ParameterDescriptor}) ReturnDescriptor”, where the {ParameterDescriptor} is a list of field descriptors representing the parameters and the ReturnDescriptor is a field descriptor identifying the return type. For instance, the string “V” may be used to represent the void return type. Thus, a method defined in the source code files101as “Object m(int I, double d, Thread t) { . . . }” matches the descriptor “(I D L Thread) L Object”.

In an embodiment, the virtual machine instructions held in the method structures209include operations which reference entries of the constant table201. Using Java as an example, consider the following class:

class A{int add12and13( ) {return B.addTwo(12, 13);}}

In the above example, the Java method add12and13 is defined in class A, takes no parameters, and returns an integer. The body of method add12and13 calls static method addTwo of class B which takes the constant integer values 12 and 13 as parameters, and returns the result. Thus, in the constant table201, the compiler102includes, among other entries, a method reference structure that corresponds to the call to the method B.addTwo. In Java, a call to a method compiles down to an invoke command in the bytecode of the JVM (in this case invokestatic as addTwo is a static method of class B). The invoke command is provided an index into the constant table201corresponding to the method reference structure that identifies the class defining addTwo “B”, the name of addTwo “addTwo”, and the descriptor of addTwo “(I I)I”. For example, assuming the aforementioned method reference is stored at index 4, the bytecode instruction may appear as “invokestatic #4”.

Since the constant table201refers to classes, methods, and fields symbolically with structures carrying identifying information, rather than direct references to a memory location, the entries of the constant table201are referred to as “symbolic references”. One reason that symbolic references are utilized for the class files103is because, in some embodiments, the compiler102is unaware of how and where the classes will be stored once loaded into the runtime environment113. As will be described in Section 2.3, eventually the run-time representations of the symbolic references are resolved into actual memory addresses by the virtual machine104after the referenced classes (and associated structures) have been loaded into the runtime environment and allocated concrete memory locations.

2.3. Example Virtual Machine Architecture

FIG.3illustrates an example virtual machine memory layout300in block diagram form according to an embodiment. In order to provide clear examples, the remaining discussion will assume that the virtual machine104adheres to the virtual machine memory layout300depicted inFIG.3. In addition, although components of the virtual machine memory layout300may be referred to as memory “areas”, there is no requirement that the memory areas are contiguous.

In the example illustrated byFIG.3, the virtual machine memory layout300is divided into a shared area301and a thread area307. The shared area301represents an area in memory where structures shared among the various threads executing on the virtual machine104are stored. The shared area301includes a heap302and a per-class area303. In an embodiment, the heap302represents the run-time data area from which memory for class instances and arrays is allocated. In an embodiment, the per-class area303represents the memory area where the data pertaining to the individual classes are stored. In an embodiment, the per-class area303includes, for each loaded class, a run-time constant pool304representing data from the constant table201of the class, field and method data306(for example, to hold the static fields of the class), and the method code305representing the virtual machine instructions for methods of the class.

The thread area307represents a memory area where structures specific to individual threads are stored. InFIG.3, the thread area307includes thread structures308and thread structures311, representing the per-thread structures utilized by different threads. In order to provide clear examples, the thread area307depicted inFIG.3assumes two threads are executing on the virtual machine104. However, in a practical environment, the virtual machine104may execute any arbitrary number of threads, with the number of thread structures scaled accordingly.

In an embodiment, thread structures308includes program counter309and virtual machine stack310. Similarly, thread structures311includes program counter312and virtual machine stack313. In an embodiment, program counter309and program counter312store the current address of the virtual machine instruction being executed by their respective threads.

Thus, as a thread steps through the instructions, the program counters are updated to maintain an index to the current instruction. In an embodiment, virtual machine stack310and virtual machine stack313each store frames for their respective threads that hold local variables and partial results, and is also used for method invocation and return.

In an embodiment, a frame is a data structure used to store data and partial results, return values for methods, and perform dynamic linking. A new frame is created each time a method is invoked. A frame is destroyed when the method that caused the frame to be generated completes. Thus, when a thread performs a method invocation, the virtual machine104generates a new frame and pushes that frame onto the virtual machine stack associated with the thread.

When the method invocation completes, the virtual machine104passes back the result of the method invocation to the previous frame and pops the current frame off of the stack. In an embodiment, for a given thread, one frame is active at any point. This active frame is referred to as the current frame, the method that caused generation of the current frame is referred to as the current method, and the class to which the current method belongs is referred to as the current class.

FIG.4illustrates an example frame400in block diagram form according to an embodiment. In order to provide clear examples, the remaining discussion will assume that frames of virtual machine stack310and virtual machine stack313adhere to the structure of frame400.

In an embodiment, frame400includes local variables401, operand stack402, and run-time constant pool reference table403. In an embodiment, the local variables401are represented as an array of variables that each hold a value, for example, Boolean, byte, char, short, int, float, or reference. Further, some value types, such as longs or doubles, may be represented by more than one entry in the array. The local variables401are used to pass parameters on method invocations and store partial results. For example, when generating the frame400in response to invoking a method, the parameters may be stored in predefined positions within the local variables401, such as indexes1-N corresponding to the first to Nth parameters in the invocation.

In an embodiment, the operand stack402is empty by default when the frame400is created by the virtual machine104. The virtual machine104then supplies instructions from the method code305of the current method to load constants or values from the local variables401onto the operand stack402. Other instructions take operands from the operand stack402, operate on them, and push the result back onto the operand stack402. Furthermore, the operand stack402is used to prepare parameters to be passed to methods and to receive method results. For example, the parameters of the method being invoked could be pushed onto the operand stack402prior to issuing the invocation to the method. The virtual machine104then generates a new frame for the method invocation where the operands on the operand stack402of the previous frame are popped and loaded into the local variables401of the new frame. When the invoked method terminates, the new frame is popped from the virtual machine stack and the return value is pushed onto the operand stack402of the previous frame.

In an embodiment, the run-time constant pool reference table403contains a reference to the run-time constant pool304of the current class. The run-time constant pool reference table403is used to support resolution. Resolution is the process whereby symbolic references in the constant pool304are translated into concrete memory addresses, loading classes as necessary to resolve as-yet-undefined symbols and translating variable accesses into appropriate offsets into storage structures associated with the run-time location of these variables.

2.4. Loading, Linking, and Initializing

In an embodiment, the virtual machine104dynamically loads, links, and initializes classes. Loading is the process of finding a class with a particular name and creating a representation from the associated class file200of that class within the memory of the runtime environment113. For example, creating the run-time constant pool304, method code305, and field and method data306for the class within the per-class area303of the virtual machine memory layout300. Linking is the process of taking the in-memory representation of the class and combining it with the run-time state of the virtual machine104so that the methods of the class can be executed. Initialization is the process of executing the class constructors to set the starting state of the field and method data306of the class and/or create class instances on the heap302for the initialized class.

The following are examples of loading, linking, and initializing techniques that may be implemented by the virtual machine104. However, in many embodiments the steps may be interleaved, such that an initial class is loaded, then during linking a second class is loaded to resolve a symbolic reference found in the first class, which in turn causes a third class to be loaded, and so forth. Thus, progress through the stages of loading, linking, and initializing can differ from class to class. Further, some embodiments may delay (perform “lazily”) one or more functions of the loading, linking, and initializing process until the class is actually required. For example, resolution of a method reference may be delayed until a virtual machine instruction invoking the method is executed. Thus, the exact timing of when the steps are performed for each class can vary greatly between implementations.

To begin the loading process, the virtual machine104starts up by invoking the class loader107which loads an initial class. The technique by which the initial class is specified will vary from embodiment to embodiment. For example, one technique may have the virtual machine104accept a command line argument on startup that specifies the initial class.

To load a class, the class loader107parses the class file200corresponding to the class and determines whether the class file200is well-formed (meets the syntactic expectations of the virtual machine104). If not, the class loader107generates an error. For example, in Java the error might be generated in the form of an exception which is thrown to an exception handler for processing. Otherwise, the class loader107generates the in-memory representation of the class by allocating the run-time constant pool304, method code305, and field and method data306for the class within the per-class area303.

In some embodiments, when the class loader107loads a class, the class loader107also recursively loads the super-classes of the loaded class. For example, the virtual machine104may ensure that the super-classes of a particular class are loaded, linked, and/or initialized before proceeding with the loading, linking and initializing process for the particular class.

During linking, the virtual machine104verifies the class, prepares the class, and performs resolution of the symbolic references defined in the run-time constant pool304of the class.

To verify the class, the virtual machine104checks whether the in-memory representation of the class is structurally correct. For example, the virtual machine104may check that each class except the generic class Object has a superclass, check that final classes have no sub-classes and final methods are not overridden, check whether constant pool entries are consistent with one another, check whether the current class has correct access permissions for classes/fields/structures referenced in the constant pool304, check that the virtual machine104code of methods will not cause unexpected behavior (e.g. making sure a jump instruction does not send the virtual machine104beyond the end of the method), and so forth. The exact checks performed during verification are dependent on the implementation of the virtual machine104. In some cases, verification may cause additional classes to be loaded, but does not necessarily require those classes to also be linked before proceeding. For example, assume Class A contains a reference to a static field of Class B. During verification, the virtual machine104may check Class B to ensure that the referenced static field actually exists, which might cause loading of Class B, but not necessarily the linking or initializing of Class B. However, in some embodiments, certain verification checks can be delayed until a later phase, such as being checked during resolution of the symbolic references. For example, some embodiments may delay checking the access permissions for symbolic references until those references are being resolved.

To prepare a class, the virtual machine104initializes static fields located within the field and method data306for the class to default values. In some cases, setting the static fields to default values may not be the same as running a constructor for the class. For example, the verification process may zero out or set the static fields to values that the constructor would expect those fields to have during initialization.

During resolution, the virtual machine104dynamically determines concrete memory address from the symbolic references included in the run-time constant pool304of the class. To resolve the symbolic references, the virtual machine104utilizes the class loader107to load the class identified in the symbolic reference (if not already loaded). Once loaded, the virtual machine104has knowledge of the memory location within the per-class area303of the referenced class and its fields/methods. The virtual machine104then replaces the symbolic references with a reference to the concrete memory location of the referenced class, field, or method. In an embodiment, the virtual machine104caches resolutions to be reused in case the same class/name/descriptor is encountered when the virtual machine104processes another class. For example, in some cases, class A and class B may invoke the same method of class C. Thus, when resolution is performed for class A, that result can be cached and reused during resolution of the same symbolic reference in class B to reduce overhead.

In some embodiments, the step of resolving the symbolic references during linking is optional. For example, an embodiment may perform the symbolic resolution in a “lazy” fashion, delaying the step of resolution until a virtual machine instruction that requires the referenced class/method/field is executed.

During initialization, the virtual machine104executes the constructor of the class to set the starting state of that class. For example, initialization may initialize the field and method data306for the class and generate/initialize any class instances on the heap302created by the constructor. For example, the class file200for a class may specify that a particular method is a constructor that is used for setting up the starting state. Thus, during initialization, the virtual machine104executes the instructions of that constructor.

In some embodiments, the virtual machine104performs resolution on field and method references by initially checking whether the field/method is defined in the referenced class. Otherwise, the virtual machine104recursively searches through the super-classes of the referenced class for the referenced field/method until the field/method is located, or the top-level superclass is reached, in which case an error is generated.

3. Example Runtime Stack

FIG.5A-5Billustrate an example of a runtime stack500in accordance with one or more embodiments. As illustrated inFIGS.5A-5B, the runtime stack500includes a root frame502, one or more intermediate frames504, a current frame506, one or more marker frames508, a cache510, one or more cache keys512, and one or more sets of stack walking results514. In one or more embodiments, the runtime stack500may include more or fewer components than the components illustrated inFIGS.5A-5B. The components illustrated inFIGS.5A-5Bmay be local to or remote from each other. The components illustrated inFIGS.5A-5Bmay be implemented in software and/or hardware. Each component may be distributed over multiple applications and/or machines. Multiple components may be combined into one application and/or machine. Operations described with respect to one component may instead be performed by another component.

The root frame502is the oldest (or “first”) frame in the runtime stack500. InFIG.5A, the runtime stack500is visualized as filling from top to bottom (thus growing “deeper”), and the root frame502is the “top” of the runtime stack500. If the runtime stack500were instead visualized as filling from bottom to top, then the root frame502would be the “bottom” of the runtime stack500.

The current frame506is the newest frame in the runtime stack500. InFIG.5A, the runtime stack500is visualized as filling from top to bottom, and the current frame506is the “bottom” of the runtime stack500. If the runtime stack500were instead visualized as filling from bottom to top, then the current frame506would be the “top” of the runtime stack500.

Intermediate frames504are frames that were installed on the runtime stack500after the root frame502and before the current frame506. The runtime stack500may include many hundreds or even thousands of frames including the root frame502, intermediate frames504, and the current frame506.

As shown inFIG.5A, a full stack walk has a runtime cost of O(n), where n is the total number of frames on the runtime stack500. As the size of the runtime stack increases (i.e., the stack grows “deeper”), that cost increases linearly. Without optimization techniques described herein, that cost is incurred each time a stack trace is performed.

Turning toFIG.5B, using techniques described herein, the runtime environment (not shown) may be configured to store stack walking results514in a cache510. The cache510includes one or more cache keys512, each of which may be mapped to one or more respective sets of stack walking results514. A cache key512is associated with a particular marker frame508. In an embodiment, the cache key512is a representation of the calling context state on the runtime stack500, i.e., all frames from the root frame502, up to and including the marker frame508. For example, a folded representation of the calling context state (e.g., a hash value or other kind of key value) may be based, at least in part, on the return addresses of the frames. The cache key512uniquely identifies that state by representing, for example, one or more unique properties of the frames themselves and/or edges between the frames. As such, the cache key512is a function of the calling context, represented by frames on the runtime stack500. With this approach, distinct threads may map the same cache key512, if they have identical calling contexts (running the same code segment), thus allowing for cache buildup and reuse across threads. The cache key512itself is not necessarily shared across the entire runtime environment; multiple threads may produce the same value of respective cache keys512.

In an embodiment, the runtime environment is configured to use the cache key512associated with the marker frame508to perform a lookup of the cached stack walking results514corresponding to that specific location in the runtime stack500. In addition, the runtime environment may use the cache key512itself to dynamically recalculate the cache key512for another position in the runtime stack500. Specifically, the runtime environment may be configured to generate another cache key512, to incrementally account for frames installed and/or removed on the runtime stack500since the cache key512was last calculated. Thus, when the marker frame508is encountered during a stack walk, the cache key512allows for a lookup of the cached stack walking results514corresponding to that location in the runtime stack500. The runtime stack500may include multiple marker frames508, each corresponding to a different set of stack walking results514.

As discussed above, the cache key512is a value that represents the total state of the runtime stack500, up to and including the marker frame500. As the runtime stack500changes over time, the runtime environment may maintain a running value (e.g., an incrementally updated hash value) corresponding to that state. Thus, the cache510may store multiple sets of stack walking results514corresponding to different code paths. Even after unwinding the runtime stack500, if the state returns to a state for which a cached set of stack walking results514already exists, those cached results may be reused. Over time, the cache510may effectively grow into a “library” of cached results. Such a library may be particularly useful, for example, in a multithreaded environment where different threads may follow the same code paths at different times. A set of stack walking results514generated by one thread may be available to another thread, thus resulting in significant performance improvements across the entire multithreaded environment. To help preserve system resources, the system may be configured to store up to a threshold number and/or age (e.g., measured in seconds or some other time increment) of stack walking results514for each thread and/or for the runtime environment as a whole.

During runtime, the identity of the current frame506changes. Upon installing a new frame on the runtime stack500, the frame that was previously the current frame506becomes an intermediate frame504. Upon removing or “unwinding” the current frame506from the runtime stack500, the most recent intermediate frame504becomes the current frame506.

As shown inFIG.5Band described in further detail below, incremental stack walking can reduce the runtime cost of a stack walk. Specifically, the runtime cost of incremental stack walking is O(d)+O(1), where d is the number of frames installed on the runtime stack500since the most recent stack walking results514were stored in the cache510. O(1) is the runtime cost to lookup the cached stack walking results514.

4. Incremental Stack Walking

FIGS.6A-6Billustrate an example set of operations for incremental stack walking in accordance with one or more embodiments. One or more operations illustrated inFIGS.6A-6Bmay be modified, rearranged, or omitted all together. Accordingly, the particular sequence of operations illustrated inFIGS.6A-6Bshould not be construed as limiting the scope of one or more embodiments.

In an embodiment, a runtime environment receives a request to perform a stack walk (Operation602). For example, user code may include an instruction to perform a stack trace. Alternatively or additionally, the runtime environment may be configured to perform stack traces periodically and/or upon detecting one or more trigger conditions (e.g., an exception, a fault, the stack depth increasing at an unexpected rate, the stack depth reaching a threshold number of frames, etc.).

Responsive to the request to perform a stack walk, the runtime environment begins traversing the runtime stack (Operation604) starting from the current frame and iterating toward the root frame. At each frame traversed, the runtime environment determines whether that frame is a marker frame (Operation606). If the frame is not a marker frame, the runtime environment determines whether the frame is the root frame (Operation608). If the frame is not the root frame, the runtime environment continues traversing the runtime stack. If the frame is the root frame, the traversal is complete and the runtime environment may cache the stack walking results obtained during the traversal, as described in further detail below.

Returning to Operation606, if a marker frame is encountered, the runtime environment may perform a cache key lookup (Operation610). A cache key lookup uses a key uniquely corresponding to the state of the runtime stack at the marker frame's location, to determine whether a corresponding cached set of stack walking results is available. As described in further detail below, during stack unwinding, there may be some circumstances where a cache corresponding to the marker frame is not available. In an embodiment, to perform the cache key lookup, the runtime environment generates a cache key (for example, a state-specific hash value) uniquely corresponding to the state of the runtime stack at the marker frame's location and looks up the cache key in a cache table.

If there is no cached set of stack walking results associated with the cache key, then a cache miss occurs. In this situation, as discussed in further detail below, the runtime environment continues to traverse the runtime stack as if it had not encountered the marker frame and builds up a set of stack walking results starting from the frame where the traversal originated. Building and caching the set of stack walking results can reduce the runtime cost of a subsequent stack walk. An example of a performance comparison according to an embodiment is described below.

If the hash value (or another kind of cache key) is associated with a corresponding cached set of stack walking results, the runtime environment retrieves the cached set of stack walking results (Operation614). Because the marker frame marks the boundary of frames that were previously traversed and for which the cache holds the prior stack walking results, it is not necessary to continue traversing the runtime stack. The cached results, plus the results corresponding to any newer frames that were traversed in the stack walk, represent a full stack trace without having to incur the O(n) cost of a full stack walk.

In an embodiment, if the stack walk traversed any frames for which results were not already cached (for example, frames installed on the runtime stack after the marker frame was installed, or if no marker frame was encountered at all, or if no cache corresponding to the marker frame was found), the runtime environment stores a cache of the stack walking results (Operation616). If a marker frame with a corresponding cache was encountered, the runtime environment may store only an incremental cache corresponding to the newly traversed frames. Alternatively, the runtime environment may append the incremental results to the existing cached results. The runtime environment may install a marker frame on the runtime stack (Operation618) indicating that cached results are available for that location in the runtime stack. The runtime environment may further generate a cache key corresponding to the marker frame, to facilitate future cache key lookups.

5. Stack Unwinding

FIG.7illustrates an example set of operations for stack unwinding in accordance with one or more embodiments. One or more operations illustrated inFIG.7may be modified, rearranged, or omitted all together. Accordingly, the particular sequence of operations illustrated inFIG.7should not be construed as limiting the scope of one or more embodiments.

In an embodiment, at some point after installing a marker frame, the runtime environment begins unwinding the runtime stack (Operation702). For example, as function calls terminate, the corresponding stack frame(s) is/are removed from the runtime stack. While unwinding the runtime stack, the runtime environment may encounter a marker frame (Operation704). If a marker frame is encountered, the runtime environment may relocate the marker frame (Operation706). Specifically, the runtime environment may relocate the marker frame to an older position in the runtime stack. The runtime environment may relocate the marker frame by a certain number of positions at a time (e.g., one position at a time, or by another distance greater than one to reduce overhead). In an embodiment, the default distance to relocate the marker frame is one frame but may be configurable so as to allow for performance tuning. Alternatively or additionally, the runtime environment may compute the distance dynamically, based on observed performance (e.g., when a performance metric—such as compute cycles, time, etc.—falls below a predetermined threshold value). For example, a user may determine that relocating the marker frame in increments of 25 positions is sufficient for their purposes. The runtime environment may determine that 25 positions is too expensive and dynamically adjust the distance to a higher number (e.g., 35). A shorter distance increases the speed of subsequent stack walks but incurs more immediate overhead as the cache key is recalculated on each unwind.

If the cache key is based, at least in part, on the marker frame's location in the runtime stack, then the runtime environment may eventually relocate the marker frame to a location having a corresponding cached set of stack walking results. Alternatively or additionally, the runtime environment may install a new marker frame each time a stack trace is performed. In this approach, upon encountering a marker frame while unwinding the runtime stack, the runtime environment may discard the marker frame (not shown). Returning to Operation704, if no marker frame is encountered while unwinding the runtime stack, the runtime environment may proceed with unwinding the runtime stack without relocating any marker frame that was not encountered (Operation708).

6. Performance Comparison

As discussed above, incremental stack walking can improve stack walking performance considerably. In one example, three stack walks are performed in sequence. The program continues to execute after the first stack walk, pushing three newer frames onto the runtime stack before the second stack walk. The third stack walk is performed immediately after the second stack walk. Table1, below, illustrates the performance difference between (a) a typical stack walking approach that traverses the full runtime stack each time and (b) incremental stack walking using a marker frame as described herein. In Table1, the value in each cell represents the cumulative performance of each approach.

TABLE 1Performance ComparisonWalksTypical ApproachIncremental Stack WalkingInitialO(n)O(n)SecondO(n) + O(n + 3)O(n) + O(3 + 1)ThirdO(n) + O(n + 3) + O(n + 3)O(n) + O(3 + 1) + O(1)

From a performance perspective, with incremental stack walking, the stack depth appears to have collapsed or shrunk in comparison to each prior walk. Previously traversed frames do not need to be traversed again, thus providing a dynamic reduction in the number of frames the runtime environment must traverse in subsequent stack walks.

7. Computer Networks and Cloud Networks

In one or more embodiments, a computer network provides connectivity among a set of nodes. The nodes may be local to and/or remote from each other. The nodes are connected by a set of links. Examples of links include a coaxial cable, an unshielded twisted cable, a copper cable, an optical fiber, and a virtual link.

A subset of nodes implements the computer network. Examples of such nodes include a switch, a router, a firewall, and a network address translator (NAT). Another subset of nodes uses the computer network. Such nodes (also referred to as “hosts”) may execute a client process and/or a server process. A client process makes a request for a computing service, such as execution of a particular application and/or storage of a particular amount of data). A server process responds by, for example, executing the requested service and/or returning corresponding data.

A computer network may be a physical network, including physical nodes connected by physical links. A physical node is any digital device. A physical node may be a function-specific hardware device, such as a hardware switch, a hardware router, a hardware firewall, or a hardware NAT. Additionally or alternatively, a physical node may be a generic machine that is configured to execute various virtual machines and/or applications performing respective functions. A physical link is a physical medium connecting two or more physical nodes. Examples of links include a coaxial cable, an unshielded twisted cable, a copper cable, and an optical fiber.

A computer network may be an overlay network. An overlay network is a logical network implemented on top of another network, such as a physical network. Each node in an overlay network corresponds to a respective node in the underlying network. Hence, each node in an overlay network is associated with both an overlay address (to address to the overlay node) and an underlay address (to address the underlay node that implements the overlay node). An overlay node may be a digital device and/or a software process (such as a virtual machine, an application instance, or a thread) A link that connects overlay nodes is implemented as a tunnel through the underlying network. The overlay nodes at either end of the tunnel treat the underlying multi-hop path between them as a single logical link. Tunneling is performed through encapsulation and decapsulation.

A client may be local to and/or remote from a computer network. The client may access the computer network over other computer networks, such as a private network or the Internet. The client may communicate requests to the computer network using a communications protocol, such as Hypertext Transfer Protocol (HTTP). The requests are communicated through an interface, such as a client interface (for example, a web browser), a program interface, or an application programming interface (API).

In one or more embodiments, a computer network provides connectivity between clients and network resources. Network resources include hardware and/or software configured to execute server processes. Examples of network resources include a processor, a data storage, a virtual machine, a container, and/or a software application. Network resources are shared amongst multiple clients. Clients request computing services from a computer network independently of each other. Network resources are dynamically assigned to the requests and/or clients on an on-demand basis. Network resources assigned to each request and/or client may be scaled up or down based on, for example, (a) the computing services requested by a particular client, (b) the aggregated computing services requested by a particular tenant, and/or (c) the aggregated computing services requested of the computer network. Such a computer network may be referred to as a “cloud network.”

In one or more embodiments, a service provider provides a cloud network to one or more end users. Various service models may be implemented by the cloud network, including but not limited to Software-as-a-Service (SaaS), Platform-as-a-Service (PaaS), and Infrastructure-as-a-Service (IaaS). In SaaS, a service provider provides end users the capability to use the service provider's applications, which are executing on the network resources. In PaaS, the service provider provides end users the capability to deploy custom applications onto the network resources. The custom applications may be created using programming languages, libraries, services, and tools supported by the service provider. In IaaS, the service provider provides end users the capability to provision processing, storage, networks, and other fundamental computing resources provided by the network resources. Any arbitrary applications, including an operating system, may be deployed on the network resources.

A computer network may implement various deployment, including but not limited to a private cloud, a public cloud, and/or a hybrid cloud. In a private cloud, network resources are provisioned for exclusive use by a particular group of one or more entities (the term “entity” as used herein refers to a corporation, organization, person, or other entity). The network resources may be local to and/or remote from the premises of the particular group of entities. In a public cloud, cloud resources are provisioned for multiple entities that are independent from each other (also referred to as “tenants” or “customers”). The computer network and the network resources thereof may be accessed by clients corresponding to different tenants. Such a computer network may be referred to as a “multi-tenant computer network.” Several tenants may use a same particular network resource at different times and/or at the same time. The network resources may be local to and/or remote from the premises of the tenants. In a hybrid cloud, a computer network comprises a private cloud and a public cloud. An interface between the private cloud and the public cloud allows for data and application portability. Data stored at the private cloud and data stored at the public cloud may be exchanged through the interface. Applications implemented at the private cloud and applications implemented at the public cloud may have dependencies on each other. A call from an application at the private cloud to an application at the public cloud (and vice versa) may be executed through the interface.

In one or more embodiments, tenants of a multi-tenant computer network are independent of each other. For example, a business or operation of one tenant may be separate from a business or operation of another tenant. Different tenants may demand different network requirements for the computer network. Examples of network requirements include processing speed, amount of data storage, security requirements, performance requirements, throughput requirements, latency requirements, resiliency requirements, Quality of Service (QoS) requirements, tenant isolation, and/or consistency. The same computer network may need to implement different network requirements demanded by different tenants.

In a multi-tenant computer network, tenant isolation may be implemented to ensure that the applications and/or data of different tenants are not shared with each other. Various tenant isolation approaches may be used. Each tenant may be associated with a tenant identifier (ID). Each network resource of the multi-tenant computer network may be tagged with a tenant ID. A tenant may be permitted access to a particular network resource only if the tenant and the particular network resources are associated with the same tenant ID.

For example, each application implemented by the computer network may be tagged with a tenant ID, and tenant may be permitted access to a particular application only if the tenant and the particular application are associated with a same tenant ID. Each data structure and/or dataset stored by the computer network may be tagged with a tenant ID, and tenant may be permitted access to a particular data structure and/or dataset only if the tenant and the particular data structure and/or dataset are associated with a same tenant ID. Each database implemented by the computer network may be tagged with a tenant ID, and tenant may be permitted access to data of a particular database only if the tenant and the particular database are associated with the same tenant ID. Each entry in a database implemented by a multi-tenant computer network may be tagged with a tenant ID, and a tenant may be permitted access to a particular entry only if the tenant and the particular entry are associated with the same tenant ID. However, the database may be shared by multiple tenants.

In one or more embodiments, a subscription list indicates which tenants have authorization to access which network resources. For each network resource, a list of tenant IDs of tenants authorized to access the network resource may be stored. A tenant may be permitted access to a particular network resource only if the tenant ID of the tenant is included in the subscription list corresponding to the particular network resource.

In one or more embodiments, network resources (such as digital devices, virtual machines, application instances, and threads) corresponding to different tenants are isolated to tenant-specific overlay networks maintained by the multi-tenant computer network. As an example, packets from any source device in a tenant overlay network may be transmitted only to other devices within the same tenant overlay network. Encapsulation tunnels may be used to prohibit any transmissions from a source device on a tenant overlay network to devices in other tenant overlay networks. Specifically, packets received from the source device may be encapsulated within an outer packet. The outer packet is transmitted from a first encapsulation tunnel endpoint (in communication with the source device in the tenant overlay network) to a second encapsulation tunnel endpoint (in communication with the destination device in the tenant overlay network). The second encapsulation tunnel endpoint decapsulates the outer packet to obtain the original packet transmitted by the source device. The original packet is transmitted from the second encapsulation tunnel endpoint to the destination device in the same particular overlay network.

8. Hardware Overview

In one or more embodiments, techniques described herein are implemented by one or more special-purpose computing devices. The special-purpose computing device(s) may be hard-wired to perform the techniques, and/or may include digital electronic devices such as one or more application-specific integrated circuits (ASICs), field programmable gate arrays (FPGAs), or network processing units (NPUs) that are persistently programmed to perform the techniques, or may include one or more general purpose hardware processors programmed to perform the techniques pursuant to program instructions in firmware, memory, other storage, or a combination thereof. Such special-purpose computing devices may also combine custom hard-wired logic, ASICs, FPGAs, or NPUs with custom programming to accomplish the techniques. A special-purpose computing device may be desktop computer systems, portable computer systems, handheld devices, networking devices, or any other device that incorporates hard-wired and/or program logic to implement the techniques.

For example,FIG.8is a block diagram that illustrates a computer system800upon which one or more embodiments of the invention may be implemented. The computer system800includes a bus802or other communication mechanism for communicating information, and a hardware processor804coupled with bus802for processing information. The hardware processor804may be, for example, a general-purpose microprocessor.

The computer system800also includes a main memory806, such as a random access memory (RAM) or other dynamic storage device, coupled to bus802for storing information and instructions to be executed by processor804. The main memory806also may be used for storing temporary variables or other intermediate information during execution of instructions to be executed by processor804. Such instructions, when stored in non-transitory storage media accessible to the processor804, render the computer system800into a special-purpose machine that is customized to perform the operations specified in the instructions.

The computer system800further includes a read only memory (ROM)808or other static storage device coupled to the bus802for storing static information and instructions for the processor804. A storage device810, such as a magnetic disk or optical disk, is provided and coupled to the bus802for storing information and instructions.

The computer system800may be coupled via the bus802to a display812, such as a cathode ray tube (CRT), for displaying information to a computer user. An input device814, including alphanumeric and other keys, is coupled to the bus802for communicating information and command selections to the processor804. Another type of user input device is cursor control816, such as a mouse, a trackball, or cursor direction keys for communicating direction information and command selections to the processor804and for controlling cursor movement on the display812. This input device typically has two degrees of freedom in two axes, a first axis (e.g., x) and a second axis (e.g., y), that allows the device to specify positions in a plane.

The computer system800may implement techniques described herein using customized hard-wired logic, one or more ASICs or FPGAs, firmware, and/or program logic which in combination with the computer system800causes or programs the computer system800to be a special-purpose machine. In one or more embodiments, the techniques herein are performed by the computer system800in response to the processor804executing one or more sequences of one or more instructions contained in the main memory806. Such instructions may be read into the main memory806from another storage medium, such as the storage device810. Execution of the sequences of instructions contained in the main memory806causes the processor804to perform the process steps described herein. Alternatively, hard-wired circuitry may be used in place of or in combination with software instructions.

The term “storage media” as used herein refers to any non-transitory media that store data and/or instructions that cause a machine to operate in a specific fashion. Such storage media may include non-volatile media and/or volatile media. Non-volatile media includes, for example, optical or magnetic disks, such as storage device810. Volatile media includes dynamic memory, such as the main memory806. Common forms of storage media include, for example, a floppy disk, a flexible disk, hard disk, solid state drive, magnetic tape, or any other magnetic data storage medium, a read-only compact disc (CD-ROM), any other optical data storage medium, any physical medium with patterns of holes, a RAM, a PROM, and EPROM, a FLASH-EPROM, NVRAM, any other memory chip or cartridge, content-addressable memory (CAM), and ternary content-addressable memory (TCAM).

Storage media is distinct from but may be used in conjunction with transmission media. Transmission media participates in transferring information between storage media. For example, transmission media includes coaxial cables, copper wire and fiber optics, including the wires of the bus802. Transmission media can also take the form of acoustic or light waves, such as those generated during radio frequency (RF) and infrared data communications.

Various forms of media may be involved in carrying one or more sequences of one or more instructions to the processor804for execution. For example, the instructions may initially be carried on a magnetic disk or solid-state drive of a remote computer. The remote computer can load the instructions into its dynamic memory and send the instructions over a telephone line or other communications medium, using a modem. A modem local to the computer system800can receive the data on the telephone line or other communications medium and use an infrared transmitter to convert the data to an infrared signal. An infrared detector can receive the data carried in the infrared signal and appropriate circuitry can place the data on the bus802. The bus802carries the data to the main memory806, from which the processor804retrieves and executes the instructions. The instructions received by the main memory806may optionally be stored on the storage device810, either before or after execution by processor804.

The computer system800also includes a communication interface818coupled to the bus802. The communication interface818provides a two-way data communication coupling to a network link820that is connected to a local network822. For example, the communication interface818may be an integrated services digital network (ISDN) card, cable modem, satellite modem, or a modem to provide a data communication connection to a corresponding type of telephone line. As another example, the communication interface818may be a local area network (LAN) card configured to provide a data communication connection to a compatible LAN. Wireless links may also be implemented. In any such implementation, the communication interface818sends and receives electrical, electromagnetic, or optical signals that carry digital data streams representing various types of information.

The network link820typically provides data communication through one or more networks to other data devices. For example, the network link820may provide a connection through a local network822to a host computer824or to data equipment operated by an Internet Service Provider (ISP)826. The ISP826in turn provides data communication services through the world wide packet data communication network now commonly referred to as the “Internet”828. The local network822and Internet828both use electrical, electromagnetic, or optical signals that carry digital data streams. The signals through the various networks and the signals on the network link820and through the communication interface818, which carry the digital data to and from the computer system800, are example forms of transmission media.

The computer system800can send messages and receive data, including program code, through the network(s), network link820, and communication interface818. In the Internet example, a server830might transmit a requested code for an application program through the Internet828, ISP826, local network822, and communication interface818.

The received code may be executed by processor804as it is received, and/or may be stored in the storage device810or other non-volatile storage for later execution.

9. Miscellaneous; Extensions

Embodiments are directed to a system with one or more devices that include a hardware processor and that are configured to perform any of the operations described herein and/or recited in any of the claims below.

In one or more embodiments, a non-transitory computer-readable storage medium stores instructions which, when executed by one or more hardware processors, cause performance of any of the operations described herein and/or recited in any of the claims.

Any combination of the features and functionalities described herein may be used in accordance with one or more embodiments. In the foregoing specification, embodiments have been described with reference to numerous specific details that may vary from implementation to implementation. The specification and drawings are, accordingly, to be regarded in an illustrative rather than a restrictive sense. The sole and exclusive indicator of the scope of the invention, and what is intended by the applicants to be the scope of the invention, is the literal and equivalent scope of the set of claims that issue from this application, in the specific form in which such claims issue, including any subsequent correction.