cwielenb/CNCF-Dataset huggingface dataset:
Project: SeaTunnel (App Definition and Development / Streaming & Messaging)
File: kafka-compatible-kafkaconnect-json.md

Seatunnel connector kafka supports parsing data extracted through kafka connect source, especially data extracted from kafka connect jdbc and kafka connect debezium ```bash env { parallelism = 1 job.mode = "BATCH" } source { Kafka { bootstrap.servers = "localhost:9092" topic = "jdbcsourcerecord" resulttablename = "kafka_table" start_mode = earliest schema = { fields { id = "int" name = "string" description = "string" weight = "string" } }, format = COMPATIBLEKAFKACONNECT_JSON } } sink { Jdbc { driver = com.mysql.cj.jdbc.Driver url = "jdbc:mysql://localhost:3306/seatunnel" user = st_user password = seatunnel generatesinksql = true database = seatunnel table = jdbc_sink primary_keys = ["id"] } } ```
Project: Dapr (App Definition and Development / Application Definition & Image Build)
File: v1.10.6.md

This patch release contains fixes for 2 bugs. A regression introduced in Dapr 1.10.0 caused actor reminders and timers not to deserialize its data when being triggered. The issue impacts all users on Dapr 1.10.5. A change introduced in Dapr 1.10.0 accidentally changed how reminders and timers were sent to the application, causing SDKs not to deserialized them. Fix the issue in runtime code. When unmarshling reminder from MongoDB, some of the attributes have null-equivalent values that should not be parsed. Dapr 1.10 added this regression for MongoDB. The issue impacts users on Dapr 1.10.x to use reminders with MongoDB. Accidental regression on refactor of reminders code. Fixed the runtime code to support more null-equivalent values.
Project: YugabyteDB (App Definition and Development / Database)
File: _template.md

title: TA-<num> headerTitle: <title> headcontent: <date> type: docs showRightNav: true cascade: unversioned: true rightNav: hideH2: true type: docs | Product | Affected Versions | Related Issues | Fixed In | | :- | : | :- | :- | | {{<product "ysql">}} | {{<release "All">}} | {{<issue 21297>}} | N/A |
Project: YDB (App Definition and Development / Database)
File: load-actors-interval.md

An interval written as a repeated `TIntervalInfo` field is calculated by the following algorithm: An element from the `TIntervalInfo` array isselected at random with the probability proportionate to its weight. For an element of the `TIntervalUniform` type, the value is chosen with equal probability in the range Min-Max. `Min-Max` (if `MinMs/MaxMs` is used,the value is in milliseconds; if `MinUs/MaxUs` is used, the value is in microseconds). For an element of the `TIntervalPoisson` type, the interval is selected using the formula `Min(log(-x / Frequency), MaxIntervalMs)`, where `x` is a random value in the interval `[0, 1]`. As a result, the intervals follow thePoisson distribution with the given `Frequency`, but with the interval within `MaxIntervalMs`. A similar approach is used for the probabilistic distribution of the size of the written data. However, in this case, only the data size follows a uniform probability distribution, within the interval `[Min, Max]`.
Project: Chef Habitat (App Definition and Development / Application Definition & Image Build)
File: gcr.md

+++ title = "Google Container Registry (GCR)" description = "Google Container Registry" gh_repo = "habitat" [menu] [menu.habitat] title = "Google Container Registry (GCR)" identifier = "habitat/containers/gcr GCR" parent = "habitat/containers" weight = 60 +++ is a private Docker repository that works with popular continuous delivery systems. It runs on GCP to provide consistent uptime on an infrastructure protected by Google's security. The registry service hosts your private images in Cloud Storage under your GCP project. Before you can push or pull images, you must configure Docker to use the gcloud command-line tool to authenticate requests to Container Registry. To do so, run the following command (you are only required to do this once): ```bash $ gcloud auth configure-docker ``` Further access control information is . After a successful Chef Habitat package build, images can be pushed to the Container Registry using the registry URI. The format of this follows: `: ```bash $ hab pkg export docker ./results/habskp-hab-gcr-demo-0.1.0-20180710145742-x86_64-linux.hart $ docker tag habskp/hab-gcr-demo:latest eu.gcr.io/user-project/hab-gcr-demo:latest $ docker push eu.gcr.io/user-project/hab-gcr-demo:latest ```
Project: Podman (App Definition and Development / Application Definition & Image Build)
File: podman-generate.1.md

% podman-generate 1 podman\-generate - Generate structured data based on containers, pods or volumes podman generate subcommand The generate command creates structured output (like YAML) based on a container, pod or volume. | Command | Man Page | Description | |||-| | kube | | Generate Kubernetes YAML based on containers, pods or volumes. | | spec | | Generate Specgen JSON based on containers or pods. | | systemd | | [DEPRECATED] Generate systemd unit file(s) for a container or pod. | , ,
Project: YDB (App Definition and Development / Database)
File: slots.md

A slot is the portion of a server's resources allocated to running a single {{ ydb-short-name }} cluster node. It is constant and equal to 10 CPUs/50 GB RAM. Slots are used if a {{ ydb-short-name }} cluster is deployed on bare-metal instances whose resources are sufficient to host multiple slots. If you use VMs for cluster deployment, their capacity is selected so that the use of slots is not required: one node serves one database and one database can use multiple nodes allocated to it. You can see a list of DB slots in the output of the `discovery list` command of the {{ ydb-short-name }} console client.
Project: YDB (App Definition and Development / Database)
File: examples-exp.md

This query plan implies that a `FullScan` is made for the `seasons` table and multiple reads are made for the `series` table (the `MultiLookup` type) by the key `seriesid` (lookupby). The `MultiLookup` read type and the `lookupby` section indicate that the `series` table is subject to multiple reads by the `seriesid` key.
Project: Beam (App Definition and Development / Streaming & Messaging)
File: beam-katas-kotlin-release.md

title: "Announcing Beam Katas for Kotlin" date: 2020-06-01 00:00:01 -0800 categories: blog aliases: /blog/2020/06/01/beam-katas-kotlin-release.html authors: rionmonster <!-- Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License. --> Today, we are happy to announce a new addition to the Beam Katas family: Kotlin! <!--more--> <img src="/images/blog/beam-katas-kotlin-release/beam-and-kotlin.png" alt="Apache Beam and Kotlin Shaking Hands" height="330" width="800" > You may remember that informed everyone of the wonderful Beam Katas available on for learning more about writing Apache Beam applications, working with its various APIs and programming model hands-on, all from the comfort of your favorite IDEs. As of today, you can now work through all of the progressive exercises to learn about the fundamentals of Beam in Kotlin. is a modern, open-source, statically typed language that targets the JVM. It is most commonly used by Android developers, however it has recently risen in popularity due to its extensive feature set that enables more concise and cleaner code than Java, without sacrificing performance or type safety. It recently was [ranked as one of the most beloved programming languages in the annual Stack Overflow Developer Survey](https://insights.stackoverflow.com/survey/2020#technology-most-loved-dreaded-and-wanted-languages-loved), so don't take just our word for it. The relationship between Apache Beam and Kotlin isn't a new one. You can find examples scattered across the web of engineering teams embracing the two technologies including . If you are new to Beam or are an experienced veteran looking for a change of pace, we'd encourage you to give Kotlin a try. You can find the Kotlin and the other excellent Beam Katas below (or by just searching for "Beam Katas" within or through ): I'd like to extend a very special thanks to for his creation of the original series of Katas and his support during the review process and making this effort a reality. <br /> <img src="/images/blog/beam-katas-kotlin-release/beam-katas-in-edutools.png" alt="Access Beam Katas Kotlin through a JetBrains Educational Product" height="252" width="800" >
Project: Chef InSpec (Provisioning / Security & Compliance)
File: google_runtime_config_variables.md

+++ title = "googleruntimeconfig_variables resource" draft = false gh_repo = "inspec" platform = "gcp" [menu] [menu.inspec] title = "googleruntimeconfig_variables" identifier = "inspec/resources/gcp/googleruntimeconfigvariables.md googleruntimeconfigvariables resource" parent = "inspec/resources/gcp" +++ A `googleruntimeconfig_variables` is used to test a Google Variable resource ```ruby describe googleruntimeconfig_variables(project: 'chef-gcp-inspec', config: 'inspec-gcp-runtime-config') do its('texts') { should include 'example.com' } end ``` Properties that can be accessed from the `googleruntimeconfig_variables` resource: See the resource for more information. `values` : an array of `googleruntimeconfig_variable` value `texts` : an array of `googleruntimeconfig_variable` text `names` : an array of `googleruntimeconfig_variable` name `configs` : an array of `googleruntimeconfig_variable` config This resource supports all of the above properties as filter criteria, which can be used with `where` as a block or a method. Ensure the is enabled for the current project.
Project: StarRocks (App Definition and Development / Database)
File: translate.md

displayed_sidebar: "English" Substitutes specified characters within a string. It works by taking a string (`source`) as the input and replaces the `fromstring` characters in `source` with `tostring`. This function is supported from v3.2. ```Haskell TRANSLATE(source, fromstring, tostring) ``` `source`: supports the `VARCHAR` type. The source string to be translated. If a character in the `source` is not found in `from_string`, it is simply included in the result string. `fromstring`: supports the `VARCHAR` type. Each character in `fromstring` is either replaced by its corresponding character in the `tostring`, or if there is no corresponding character (i.e. if `tostring` has fewer characters than the `fromstring`, the character is excluded from the result string). See Examples 2 and 3. If a character appears multiple times in `fromstring`, only its first occurrence is effective. See Example 5. `tostring`: supports the `VARCHAR` type. The string used to replace characters. If more characters are specified in `tostring` than in the `fromstring` argument, extra characters from `tostring` are ignored. See Example 4. Returns a value of the `VARCHAR` type. Scenarios where the result is `NULL`: Any of the input parameters is `NULL`. The length of the result string after translation exceeds the maximum length (1048576) of `VARCHAR`. ```plaintext -- Replace 'ab' in the source string with '12'. mysql > select translate('abcabc', 'ab', '12') as test; +--+ | test | +--+ | 12c12c | +--+ -- Replace 'mf1' in the source string with 'to'. 'to' has less characters than 'mf1' and '1' is excluded from the result string. mysql > select translate('s1m1a1rrfcks','mf1','to') as test; +--+ | test | +--+ | starrocks | +--+ -- Replace 'ab' in the source string with '1'. '1' has less characters than 'ab' and 'b' is excluded from the result string. mysql > select translate('abcabc', 'ab', '1') as test; ++ | test | ++ | 1c1c | ++ -- Replace 'ab' in the source string with '123'. '123' has more characters than 'ab' and '3' is ignored. mysql > select translate('abcabc', 'ab', '123') as test; +--+ | test | +--+ | 12c12c | +--+ -- Replace 'aba' in the source string with '123'. 'a' appears twice and only the first occurrence of 'a' is replaced. mysql > select translate('abcabc', 'aba', '123') as test; +--+ | test | +--+ | 12c12c | +--+ -- Use this function with repeat() and concat(). The result string exceeds the maximum length of VARCHAR and NULL is returned. mysql > select translate(concat('bcde', repeat('a', 1024*1024-3)), 'a', 'z') as test; +--+ | test | +--+ | NULL | +--+ -- Use this function with length(), repeat(), and concat() to calculate the length of the result string. mysql > select length(translate(concat('bcd', repeat('a', 1024*1024-3)), 'a', 'z')) as test; ++ | test | ++ | 1048576 | ++ ```
Project: The Update Framework (TUF) (Provisioning / Security & Compliance)
File: 0005-use-google-python-style-guide.md

Technical Story: https://github.com/theupdateframework/python-tuf/issues/1128 The Secure Systems Lab code style guide, which has been used for most of the code base, has become outdated. Through the upcoming rewrite, we have the chance to ignore consistency considerations with existing code style and can choose a more standard and up-to-date style guide. Flaws in original Secure Systems Lab style guide Curating a complete custom style guide is time consuming Well-established style rules lower contribution barrier Custom style is not supported by default in common tooling (i.e. editors and linters) Use custom style guide Use Google style guide with refinements Chosen option: "Use Google style guide with refinements", because the Google style guide is a comprehensive, well-established style guide that is mostly based on PEP-8 and was accepted by everyone on the TUF team. There is no need to replicate these recommendations. However, we do provide a very slim document with additional refinements, in order to emphasize items the we consider especially important, want to be handled differently, or in one specific way, where the Google guide would allow multiple. Course of Action: Follow existing style when working on existing code (files) Follow new style in any new code (files) Consider providing linter and formatter configuration (e.g. pylint, flake8, black, yapf) to enforce and facilitate new style
Project: Podman (App Definition and Development / Application Definition & Image Build)
File: podman-system-renumber.1.md

% podman-system-renumber 1 podman\-system\-renumber - Migrate lock numbers to handle a change in maximum number of locks podman system renumber podman system renumber renumbers locks used by containers and pods. Each Podman container and pod is allocated a lock at creation time, up to a maximum number controlled by the num_locks parameter in containers.conf. When all available locks are exhausted, no further containers and pods can be created until some existing containers and pods are removed. This can be avoided by increasing the number of locks available via modifying containers.conf and subsequently running podman system renumber to prepare the new locks (and reallocate lock numbers to fit the new struct). podman system renumber must be called after any changes to num_locks - failure to do so results in errors starting Podman as the number of locks available conflicts with the configured number of locks. podman system renumber can also be used to migrate 1.0 and earlier versions of Podman, which used a different locking scheme, to the new locking model. It is not strictly required to do this, but it is highly recommended to do so as deadlocks can occur otherwise. If possible, avoid calling podman system renumber while there are other Podman processes running. , , February 2019, Originally compiled by Matt Heon (mheon at redhat dot com)
Project: ClickHouse (App Definition and Development / Database)
File: v21.8.12.29-lts.md

sidebar_position: 1 sidebar_label: 2022 Backported in : Improve performance of JSON and XML output formats. (). Backported in : Quota limit was not reached, but the limit was exceeded. This PR fixes . (). Backported in : Fix abort in debug server and `DB::Exception: std::outofrange: basic_string` error in release server in case of bad hdfs url by adding additional check of hdfs url structure. (). Backported in : Fix bug in Keeper which can lead to inability to start when some coordination logs was lost and we have more fresh snapshot than our latest log. (). Backported in : Remove not like function into RPNElement. (). Backported in : Resolve `nullptr` in STS credentials provider for S3. (). Backported in : Disable `partialmergejoinlefttablebufferbytes` before bug in this optimization is fixed. See ). * Remove redundant option `partialmergejoin_optimizations`. (). Backported in : Fix invalid generated JSON when only column names contain invalid UTF-8 sequences. (). Backported in : `RENAME TABLE` query worked incorrectly on attempt to rename an DDL dictionary in `Ordinary` database, it's fixed. (). Backported in : Settings `inputformatallowerrorsnum` and `inputformatallowerrorsratio` did not work for parsing of domain types, such as `IPv4`, it's fixed. Fixes . (). Backported in : Fixed `there are no such cluster here` error on execution of `ON CLUSTER` query if specified cluster name is name of `Replicated` database. (). Backported in : Fix race in JSONEachRowWithProgress output format when data and lines with progress are mixed in output. (). Backported in : Fix usage of `Buffer` table engine with type `Map`. Fixes . (). Backported in : Fix possible assertion `../src/IO/ReadBuffer.h:58: bool DB::ReadBuffer::next(): Assertion '!hasPendingData()' failed.` in TSKV format. (). Backported in : Fix functions `empty` and `notEmpty` with arguments of `UUID` type. Fixes . (). Support toUInt8/toInt8 for if constant condition optimization. ().
Project: KubeBlocks by ApeCloud (App Definition and Development / Database)
File: kbcli_kubeblocks_uninstall.md

title: kbcli kubeblocks uninstall Uninstall KubeBlocks. ``` kbcli kubeblocks uninstall [flags] ``` ``` kbcli kubeblocks uninstall ``` ``` --auto-approve Skip interactive approval before uninstalling KubeBlocks -h, --help help for uninstall --remove-namespace Remove default created "kb-system" namespace or not --remove-pvcs Remove PersistentVolumeClaim or not --remove-pvs Remove PersistentVolume or not --timeout duration Time to wait for uninstalling KubeBlocks, such as --timeout=5m (default 5m0s) --wait Wait for KubeBlocks to be uninstalled, including all the add-ons. It will wait for a --timeout period (default true) ``` ``` --as string Username to impersonate for the operation. User could be a regular user or a service account in a namespace. --as-group stringArray Group to impersonate for the operation, this flag can be repeated to specify multiple groups. --as-uid string UID to impersonate for the operation. --cache-dir string Default cache directory (default "$HOME/.kube/cache") --certificate-authority string Path to a cert file for the certificate authority --client-certificate string Path to a client certificate file for TLS --client-key string Path to a client key file for TLS --cluster string The name of the kubeconfig cluster to use --context string The name of the kubeconfig context to use --disable-compression If true, opt-out of response compression for all requests to the server --insecure-skip-tls-verify If true, the server's certificate will not be checked for validity. This will make your HTTPS connections insecure --kubeconfig string Path to the kubeconfig file to use for CLI requests. --match-server-version Require server version to match client version -n, --namespace string If present, the namespace scope for this CLI request --request-timeout string The length of time to wait before giving up on a single server request. Non-zero values should contain a corresponding time unit (e.g. 1s, 2m, 3h). A value of zero means don't timeout requests. (default "0") -s, --server string The address and port of the Kubernetes API server --tls-server-name string Server name to use for server certificate validation. If it is not provided, the hostname used to contact the server is used --token string Bearer token for authentication to the API server --user string The name of the kubeconfig user to use ``` - KubeBlocks operation commands.
Project: Meshery (Provisioning / Automation & Configuration)
File: overview.md

layout: default title: Overview abstract: An overview of Meshery concepts and its functionality. permalink: /getting-started/overview language: en redirect_to: /project/overview Meshery is an extensible engineering platform for the collaborative design and operation of cloud and cloud native infrastructure and applications. Kubernetes-centric. Kubernetes not required. Infrastructure diversity is a reality for any enterprise. Whether you're running a single Kubernetes cluster or multiple Kubernetes clusters, on one cloud or multiple clouds, you'll find that Meshery supports your infrastructure diversity (or lack thereof). Meshery supports all Kubernetes-based infrastructure including most cloud services of AWS and GCP platforms. Meshery features can be categorized by: Performance Management Workload and performance characterization with both built-in and external load generators Prometheus and Grafana integration Lifecycle Management (Day 0, Day 1) Cloud and cloud native provisioning Discovery and onboarding of existing environments and workloads Configuration Management (Day 2) Cloud native patterns catalog Configuration best practices Policy engine for relationship inference and context-aware design Collaboration Multi-player infrastructure design and operation Data Plane Intelligence Registry and configuration of WebAssembly filters for Envoy Interoperability and Federation Integration with thousands of cloud services and cloud native projects Manage multiple service meshes concurrently Connect to multiple clusters independently Whether making a Day 0 adoption choice or maintaining a Day 2 deployment, Meshery has useful capabilities in either circumstance. Targeted audience for Meshery project would be any technology operators that leverage service mesh in their ecosystem; this includes developers, devops engineers, decision makers, architects, and organizations that rely on microservices platform. Through , Meshery describes infrastructure under management, enabling you to define cloud native designs and patterns and then to export those designs and share within the <a href="https://meshery.io/catalog" target="self">Meshery Catalog</a>. Meshery helps users weigh the value of their cloud native deployments against the overhead incurred in running different deployment scenarios and different configruations. Meshery provides statistical analysis of the request latency and throughput seen across various permutations of your workload, infrastructure and infrastructure configuration. In addition to request latency and throughput, Meshery also tracks memory and CPU overhead in of the nodes in your cluster. Establish a performance benchmark and track performance against this baseline as your environment changes over time.