Linkis helps easily connect to various back-end computation/storage engines(Spark, Python, TiDB...), exposes various interfaces(REST, JDBC, Java ...), with multi-tenancy, high performance, and resource control.

Clone this repo:
  1. 3282d0b Merge pull request #2644 from WeDataSphere/merge-1.2.0-Master by peacewong · 22 hours ago master
  2. 69e7d48 Merge remote-tracking branch 'origin/dev-1.2.0' into merge-1.2.0-Master by peacewong · 23 hours ago
  3. c5e0787 Recorded in upgrade docs linkis-dist/package/db/upgrade (#2613) (#2635) by yyuser5201314 · 24 hours ago
  4. 5b001e9 Upgrade version to 1.2.0 (#2634) by Zhen Wang · 2 days ago
  5. 8d7a7bb The rollbackversion function modifies the case (#2633) by 成彬彬 · 2 days ago

Linkis

License codecov Page Views Count

English | 中文

Introduction

Linkis builds a layer of computation middleware between upper applications and underlying engines. By using standard interfaces such as REST/WS/JDBC provided by Linkis, the upper applications can easily access the underlying engines such as MySQL/Spark/Hive/Presto/Flink, etc., and achieve the intercommunication of user resources like unified variables, scripts, UDFs, functions and resource files at the same time.

As a computation middleware, Linkis provides powerful connectivity, reuse, orchestration, expansion, and governance capabilities. By decoupling the application layer and the engine layer, it simplifies the complex network call relationship, and thus reduces the overall complexity and saves the development and maintenance costs as well.

Since the first release of Linkis in 2019, it has accumulated more than 700 trial companies and 1000+ sandbox trial users, which involving diverse industries, from finance, banking, tele-communication, to manufactory, internet companies and so on. Lots of companies have already used Linkis as a unified entrance for the underlying computation and storage engines of the big data platform.

linkis-intro-01

linkis-intro-03

Features

  • Support for diverse underlying computation storage engines.
    Currently supported computation/storage engines: Spark, Hive, Flink, Python, Pipeline, Sqoop, openLooKeng, JDBC, Shell, etc.
    Computation/storage engines to be supported: Presto (planned 1.2.0), ElasticSearch (planned 1.2.0), etc. Supported scripting languages: SparkSQL, HiveQL, Python, Shell, Pyspark, R, Scala and JDBC, etc.

  • Powerful task/request governance capabilities. With services such as Orchestrator, Label Manager and customized Spring Cloud Gateway, Linkis is able to provide multi-level labels based, cross-cluster/cross-IDC fine-grained routing, load balance, multi-tenancy, traffic control, resource control, and orchestration strategies like dual-active, active-standby, etc.

  • Support full stack computation/storage engine. As a computation middleware, it will receive, execute and manage tasks and requests for various computation storage engines, including batch tasks, interactive query tasks, real-time streaming tasks and storage tasks;

  • Resource management capabilities. ResourceManager is not only capable of managing resources for Yarn and Linkis EngineManger, but also able to provide label-based multi-level resource allocation and recycling, allowing itself to have powerful resource management capabilities across mutiple Yarn clusters and mutiple computation resource types;

  • Unified Context Service. Generate Context ID for each task/request, associate and manage user and system resource files (JAR, ZIP, Properties, etc.), result set, parameter variable, function, etc., across user, system, and computing engine. Set in one place, automatic reference everywhere;

  • Unified materials. System and user-level unified material management, which can be shared and transferred across users and systems.

Supported Engine Types

Engine NameSuppor Component Version
(Default Dependent Version)
Linkis Version RequirementsIncluded in Release Package
By Default
Description
SparkApache 2.0.0~2.4.7,
CDH >= 5.4.0,
(default Apache Spark 2.4.3)
>=1.0.3YesSpark EngineConn, supports SQL , Scala, Pyspark and R code
HiveApache >= 1.0.0,
CDH >= 5.4.0,
(default Apache Hive 2.3.3)
>=1.0.3YesHive EngineConn, supports HiveQL code
PythonPython >= 2.6,
(default Python2*)
>=1.0.3YesPython EngineConn, supports python code
ShellBash >= 2.0>=1.0.3YesShell EngineConn, supports Bash shell code
JDBCMySQL >= 5.0, Hive >=1.2.1,
(default Hive-jdbc 2.3.4)
>=1.0.3NoJDBC EngineConn, already supports MySQL and HiveQL, can be extended quickly Support other engines with JDBC Driver package, such as Oracle
FlinkFlink >= 1.12.2,
(default Apache Flink 1.12.2)
>=1.0.3NoFlink EngineConn, supports FlinkSQL code, also supports starting a new Yarn in the form of Flink Jar Application
Pipeline->=1.0.3NoPipeline EngineConn, supports file import and export
openLooKengopenLooKeng >= 1.5.0,
(default openLookEng 1.5.0)
>=1.1.1NoopenLooKeng EngineConn, supports querying data virtualization engine with Sql openLooKeng
SqoopSqoop >= 1.4.6,
(default Apache Sqoop 1.4.6)
>=1.1.2NoSqoop EngineConn, support data migration tool Sqoop engine
ImpalaImpala >= 3.2.0, CDH >=6.3.0ongoing-Impala EngineConn, supports Impala SQL code
PrestoPresto >= 0.180ongoing-Presto EngineConn, supports Presto SQL code
ElasticSearchElasticSearch >=6.0ongoing-ElasticSearch EngineConn, supports SQL and DSL code
MLSQLMLSQL >=1.1.0ongoing-MLSQL EngineConn, supports MLSQL code.
HadoopApache >=2.6.0,
CDH >=5.4.0
ongoing-Hadoop EngineConn, supports Hadoop MR/YARN application
TiSpark1.1ongoing-TiSpark EngineConn, supports querying TiDB with SparkSQL

Ecosystem

ComponentDescriptionLinkis 1.x(recommend 1.1.1) Compatible
DataSphereStudioDataSphere Studio (DSS for short) is WeDataSphere, a one-stop data application development management portal.DSS 1.0.1[released][Linkis recommend 1.1.1]
ScriptisSupport online script writing such as SQL, Pyspark, HiveQL, etc., submit to Linkis to perform data analysis web tools.In DSS 1.0.1[released]
SchedulisWorkflow task scheduling system based on Azkaban secondary development, with financial-grade features such as high performance, high availability and multi-tenant resource isolation.Schedulis0.6.2 [released]
QualitisData quality verification tool, providing data verification capabilities such as data integrity and correctnessQualitis 0.9.1 [released]
StreamisStreaming application development management tool. It supports the release of Flink Jar and Flink SQL, and provides the development, debugging and production management capabilities of streaming applications, such as: start-stop, status monitoring, checkpoint, etc.Streamis 0.1.0 [released][Linkis recommend 1.1.0]
ExchangisA data exchange platform that supports data transmission between structured and unstructured heterogeneous data sources, the upcoming Exchangis1. 0, will be connected with DSS workflowExchangis 1.0.0 [developing]
VisualisA data visualization BI tool based on the second development of Davinci, an open source project of CreditEase, provides users with financial-level data visualization capabilities in terms of data security.Visualis 1.0.0[developing]
ProphecisA one-stop machine learning platform that integrates multiple open source machine learning frameworks. Prophecis' MLFlow can be connected to DSS workflow through AppConn.Prophecis 0.3.0 [released]

Download

Please go to the Linkis Releases Page to download a compiled distribution or a source code package of Linkis.

Compile and Deploy

For more detailed guidance see: [Compile]


## compile backend ### Mac OS/Linux ./mvnw -N install ./mvnw clean install -Dmaven.javadoc.skip=true -Dmaven.test.skip=true ### Windows mvnw.cmd -N install mvnw.cmd clean install -Dmaven.javadoc.skip=true -Dmaven.test.skip=true ## compile web cd incubator-linkis/web npm install npm run build

Please refer to Quick Deployment to do the deployment.

Examples and Guidance

Documentation & Vedio

Architecture

Linkis services could be divided into three categories: computation governance services, public enhancement services and microservice governance services.

  • The computation governance services, support the 3 major stages of processing a task/request: submission -> preparation -> execution;
  • The public enhancement services, including the material library service, context service, and data source service;
  • The microservice governance services, including Spring Cloud Gateway, Eureka and Open Feign.

Below is the Linkis architecture diagram. You can find more detailed architecture docs in Linkis-Doc/Architecture. architecture

Based on Linkis the computation middleware, we've built a lot of applications and tools on top of it in the big data platform suite WeDataSphere. Below are the currently available open-source projects. More projects upcoming, please stay tuned.

wedatasphere_stack_Linkis

Contributing

Contributions are always welcomed, we need more contributors to build Linkis together. either code, or doc, or other supports that could help the community.
For code and documentation contributions, please follow the contribution guide.

Contact Us

  • Any questions or suggestions please kindly submit an issue.
  • By mail dev@linkis.apache.org
  • You can scan the QR code below to join our WeChat group to get more immediate response.

wechatgroup

Who is Using Linkis

We opened an issue [Who is Using Linkis] for users to feedback and record who is using Linkis.
Since the first release of Linkis in 2019, it has accumulated more than 700 trial companies and 1000+ sandbox trial users, which involving diverse industries, from finance, banking, tele-communication, to manufactory, internet companies and so on.