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Liang-Chi Hsieh 882122d6b7 [SPARK-35565][SS] Add config for ignoring metadata directory of FileStreamSink 
### What changes were proposed in this pull request?

This patch proposes to add an internal config for ignoring metadata of `FileStreamSink` when reading the output path.

### Why are the changes needed?

`FileStreamSink` produces a metadata directory which logs output files per micro-batch. When we read from the output path, Spark will look at the metadata and ignore other files not in the log.

Normally it works well. But for some use-cases, we may need to ignore the metadata when reading the output path. For example, when we change the streaming query and must to run it with new checkpoint directory, we cannot use previous metadata. If we create a new metadata too, when we read the output path later in Spark, Spark only reads the files listed in the new metadata. The files written before we use new checkpoint and metadata are ignored by Spark.

Although seems we can output to different output directory every time, but it is bad idea as we will produce many directories unnecessarily.

We need a config for ignoring the metadata of `FileStreamSink` when reading the output path.

### Does this PR introduce _any_ user-facing change?

Added a config for ignoring metadata of FileStreamSink when reading the output.

### How was this patch tested?

Unit tests.

Closes #32702 from viirya/ignore-metadata.

Authored-by: Liang-Chi Hsieh <viirya@gmail.com>
Signed-off-by: Jungtaek Lim <kabhwan.opensource@gmail.com>
2021-06-19 08:20:58 +09:00
..
catalyst [SPARK-35565][SS] Add config for ignoring metadata directory of FileStreamSink 2021-06-19 08:20:58 +09:00
core [SPARK-35565][SS] Add config for ignoring metadata directory of FileStreamSink 2021-06-19 08:20:58 +09:00
hive [SPARK-35798][SQL] Fix SparkPlan.sqlContext usage 2021-06-17 13:49:38 +00:00
hive-thriftserver [SPARK-35680][SQL] Add fields to YearMonthIntervalType 2021-06-15 23:08:12 +03:00
create-docs.sh [SPARK-34010][SQL][DODCS] Use python3 instead of python in SQL documentation build 2021-01-05 19:48:10 +09:00
gen-sql-api-docs.py [SPARK-34747][SQL][DOCS] Add virtual operators to the built-in function document 2021-03-19 10:19:26 +09:00
gen-sql-config-docs.py [SPARK-32194][PYTHON] Use proper exception classes instead of plain Exception 2021-05-26 11:54:40 +09:00
gen-sql-functions-docs.py [SPARK-31562][SQL] Update ExpressionDescription for substring, current_date, and current_timestamp 2020-04-26 11:46:52 -07:00
mkdocs.yml [SPARK-30731] Update deprecated Mkdocs option 2020-02-19 17:28:58 +09:00
README.md [SPARK-30510][SQL][DOCS] Publicly document Spark SQL configuration options 2020-02-09 19:20:47 +09:00

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 extensions that allow users to write queries using a subset of HiveQL and access data from a Hive Metastore using Hive SerDes. There are also wrappers that allow 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, and SQL configuration documentation that gets included as part of configuration.md in the main docs directory.