spark-instrumented-optimizer/sql
Xiao Li c891e025b8 Revert "[SPARK-32481][CORE][SQL] Support truncate table to move data to trash"
### What changes were proposed in this pull request?

This reverts commit 065f17386d, which is not part of any released version. That is, this is an unreleased feature

### Why are the changes needed?

I like the concept of Trash, but I think this PR might just resolve a very specific issue by introducing a mechanism without a proper design doc. This could make the usage more complex.

I think we need to consider the big picture. Trash directory is an important concept. If we decide to introduce it, we should consider all the code paths of Spark SQL that could delete the data, instead of Truncate only. We also need to consider what is the current behavior if the underlying file system does not provide the API `Trash.moveToAppropriateTrash`. Is the exception good? How about the performance when users are using the object store instead of HDFS? Will it impact the GDPR compliance?

In sum, I think we should not merge the PR https://github.com/apache/spark/pull/29552 without the design doc and implementation plan. That is why I reverted it before the code freeze of Spark 3.1

### Does this PR introduce _any_ user-facing change?
Reverted the original commit

### How was this patch tested?
The existing tests.

Closes #30463 from gatorsmile/revertSpark-32481.

Authored-by: Xiao Li <gatorsmile@gmail.com>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
2020-11-23 17:43:58 +09:00
..
catalyst Revert "[SPARK-32481][CORE][SQL] Support truncate table to move data to trash" 2020-11-23 17:43:58 +09:00
core Revert "[SPARK-32481][CORE][SQL] Support truncate table to move data to trash" 2020-11-23 17:43:58 +09:00
hive [SPARK-28704][SQL][TEST] Add back Skiped HiveExternalCatalogVersionsSuite in HiveSparkSubmitSuite at JDK9+ 2020-11-22 10:29:15 -08:00
hive-thriftserver [SPARK-33463][SQL] Keep Job Id during incremental collect in Spark Thrift Server 2020-11-21 08:39:16 -08:00
create-docs.sh [SPARK-31550][SQL][DOCS] Set nondeterministic configurations with general meanings in sql configuration doc 2020-04-27 17:08:52 +09:00
gen-sql-api-docs.py [SPARK-31474][SQL][FOLLOWUP] Replace _FUNC_ placeholder with functionname in the note field of expression info 2020-04-23 13:33:04 +09:00
gen-sql-config-docs.py [SPARK-31550][SQL][DOCS] Set nondeterministic configurations with general meanings in sql configuration doc 2020-04-27 17:08:52 +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

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.