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What is TiSpark?

TiSpark is a thin layer built for running Apache Spark on top of TiDB/TiKV to answer the complex OLAP queries. It takes advantages of both the Spark platform and the distributed TiKV cluster, at the same time, seamlessly glues to TiDB, the distributed OLTP database, to provide a Hybrid Transactional/Analytical Processing (HTAP) to serve as a one-stop solution for online transactions and analysis.

TiSpark Architecture

architecture

  • TiSpark integrates with Spark Catalyst Engine deeply. It provides precise control of the computing, which allows Spark read data from TiKV efficiently. It also supports index seek, which improves the performance of the point query execution significantly.

  • It utilizes several strategies to push down the computing to reduce the size of dataset handling by Spark SQL, which accelerates the query execution. It also uses the TiDB built-in statistical information for the query plan optimization.

  • From the data integration point of view, TiSpark + TiDB provides a solution runs both transaction and analysis directly on the same platform without building and maintaining any ETLs. It simplifies the system architecture and reduces the cost of maintenance.

  • In addition, you can deploy and utilize tools from the Spark ecosystem for further data processing and manipulation on TiDB. For example, using TiSpark for data analysis and ETL; retrieving data from TiKV as a machine learning data source; generating reports from the scheduling system and so on.

TiSpark depends on the existence of TiKV clusters and PDs. It also needs to setup and use Spark clustering platform.

A thin layer of TiSpark. Most of the logic is inside tikv-java-client library. https://github.com/pingcap/tikv-client-lib-java

Uses as below

./bin/spark-shell --jars /wherever-it-is/tispark-0.1.0-SNAPSHOT-jar-with-dependencies.jar

import org.apache.spark.sql.TiContext
val ti = new TiContext(spark) 

// Mapping all TiDB tables from database tpch as Spark SQL tables
ti.tidbMapDatabase("tpch")

spark.sql("select count(*) from lineitem").show

Current Version

ti.version

or

spark.sql("select ti_version()").show

Configuration

Below configurations can be put together with spark-defaults.conf or passed in the same way as other Spark config properties.

Key Default Value Description
spark.tispark.pd.addresses 127.0.0.1:2379 PD Cluster Addresses, split by comma
spark.tispark.grpc.framesize 268435456 Max frame size of GRPC response
spark.tispark.grpc.timeout_in_sec 10 GRPC timeout time in seconds
spark.tispark.meta.reload_period_in_sec 60 Metastore reload period in seconds
spark.tispark.plan.allow_agg_pushdown true If allow aggregation pushdown (in case of busy TiKV nodes)
spark.tispark.plan.allow_index_double_read false If allow index double read (which might cause heavy pressure on TiKV)
spark.tispark.index.scan_batch_size 2000000 How many row key in batch for concurrent index scan
spark.tispark.index.scan_concurrency 5 Maximal threads for index scan retrieving row keys (shared among tasks inside each JVM)
spark.tispark.table.scan_concurrency 512 Maximal threads for table scan (shared among tasks inside each JVM)
spark.tispark.request.command.priority "Low" "Low", "Normal", "High" which impacts resource to get in TiKV. Low is recommended for not disturbing OLTP workload
spark.tispark.coprocess.streaming false Whether to use streaming for response fetching
spark.tispark.plan.unsupported_pushdown_exprs "" A comma separated list of expressions. In case you have very old version of TiKV, you might disable some of the expression push-down if not supported
spark.tispark.plan.downgrade.index_threshold 100000 If index scan handles for one region exceeds this limit in original request, downgrade the request to a full table scan rather than original planned index scan
spark.tispark.type.unsupported_mysql_types "time,enum,set,year" A comma separated list of mysql types TiSpark does not support currently, refer to Unsupported MySQL Type List below
spark.tispark.request.timezone.offset Local Timezone offset An integer, represents timezone offset to UTC time(like 28800, GMT+8), this value will be added to requests issued to TiKV

Unsupported MySQL Type List

Mysql Type
time
enum
set
year

Quick start

Read the Quick Start.

How to build

To build all TiSpark modules :

mvn clean install -Dmaven.test.skip=true

Remember to add -Dmaven.test.skip=true to skip all the tests if you don't need to run them.

How to test

We use docker-compose to provide tidb cluster service which allows you to run test across different platforms. It is recommended to install docker in order to test locally, or you can set up your own TiDB cluster locally as you wish.

If you prefer the docker way, you can use docker-compose up -d to launch tidb cluster service under tispark home directory. If you want to see tidb cluster's log you can launch via docker-compose up. You can use docker-compose down to shutdown entire tidb cluster service. All data is stored in data directory at the root of this project. Feel free to change it.

You can read more about test here.

Follow us

Twitter

@PingCAP

Mailing list

[email protected]

Google Group

License

TiSpark is under the Apache 2.0 license. See the LICENSE file for details.

Latest Releases
pre-exp-refactor
 Jan. 16 2018
pre-dag
 Dec. 1 2017
pre-index
 Oct. 16 2017