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Yuanjian Li 07ae39d0ec [SPARK-22956][SS] Bug fix for 2 streams union failover scenario 
## What changes were proposed in this pull request?

This problem reported by yanlin-Lynn ivoson and LiangchangZ. Thanks!

When we union 2 streams from kafka or other sources, while one of them have no continues data coming and in the same time task restart, this will cause an `IllegalStateException`. This mainly cause because the code in [MicroBatchExecution](https://github.com/apache/spark/blob/master/sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/MicroBatchExecution.scala#L190) , while one stream has no continues data, its comittedOffset same with availableOffset during `populateStartOffsets`, and `currentPartitionOffsets` not properly handled in KafkaSource. Also, maybe we should also consider this scenario in other Source.

## How was this patch tested?

Add a UT in KafkaSourceSuite.scala

Author: Yuanjian Li <xyliyuanjian@gmail.com>

Closes #20150 from xuanyuanking/SPARK-22956.
2018-01-15 22:01:14 -08:00
..
catalyst [SPARK-23080][SQL] Improve error message for built-in functions 2018-01-16 11:47:42 +09:00
core [SPARK-22956][SS] Bug fix for 2 streams union failover scenario 2018-01-15 22:01:14 -08:00
hive [SPARK-23000] Use fully qualified table names in HiveMetastoreCatalogSuite 2018-01-16 11:20:18 +08:00
hive-thriftserver [SPARK-23028] Bump master branch version to 2.4.0-SNAPSHOT 2018-01-13 00:37:59 +08:00
create-docs.sh [MINOR][DOCS] Minor doc fixes related with doc build and uses script dir in SQL doc gen script 2017-08-26 13:56:24 +09:00
gen-sql-markdown.py [SPARK-21485][FOLLOWUP][SQL][DOCS] Describes examples and arguments separately, and note/since in SQL built-in function documentation 2017-08-05 10:10:56 -07:00
mkdocs.yml [SPARK-21485][SQL][DOCS] Spark SQL documentation generation for built-in functions 2017-07-26 09:38:51 -07:00
README.md [SPARK-21485][SQL][DOCS] Spark SQL documentation generation for built-in functions 2017-07-26 09:38:51 -07:00

README.md

Spark SQL

This module provides support for executing relational queries expressed in either SQL or the DataFrame/Dataset API.

Spark SQL is broken up into four subprojects:

  • Catalyst (sql/catalyst) - An implementation-agnostic framework for manipulating trees of relational operators and expressions.
  • Execution (sql/core) - A query planner / execution engine for translating Catalyst's logical query plans into Spark RDDs. This component also includes a new public interface, SQLContext, that allows users to execute SQL or LINQ statements against existing RDDs and Parquet files.
  • Hive Support (sql/hive) - Includes an extension of SQLContext called HiveContext that allows users to write queries using a subset of HiveQL and access data from a Hive Metastore using Hive SerDes. There are also wrappers that allows users to run queries that include Hive UDFs, UDAFs, and UDTFs.
  • HiveServer and CLI support (sql/hive-thriftserver) - Includes support for the SQL CLI (bin/spark-sql) and a HiveServer2 (for JDBC/ODBC) compatible server.

Running sql/create-docs.sh generates SQL documentation for built-in functions under sql/site.