3a3f8ca6f4
### What changes were proposed in this pull request?
This PR is used to fix this bug:
```
set spark.sql.legacy.charVarcharAsString=true;
create table chartb01(a char(3));
insert into chartb01 select 'aaaaa';
```
here we expect the data of table chartb01 is 'aaa', but it runs failed.
### Why are the changes needed?
Improve backward compatibility
```
spark-sql>
> create table tchar01(col char(2)) using parquet;
Time taken: 0.767 seconds
spark-sql>
> insert into tchar01 select 'aaa';
ERROR | Executor task launch worker for task 0.0 in stage 0.0 (TID 0) | Aborting task | org.apache.spark.util.Utils.logError(Logging.scala:94)
java.lang.RuntimeException: Exceeds char/varchar type length limitation: 2
at org.apache.spark.sql.catalyst.util.CharVarcharCodegenUtils.trimTrailingSpaces(CharVarcharCodegenUtils.java:31)
at org.apache.spark.sql.catalyst.util.CharVarcharCodegenUtils.charTypeWriteSideCheck(CharVarcharCodegenUtils.java:44)
at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.project_doConsume_0$(Unknown Source)
at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.processNext(Unknown Source)
at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
at org.apache.spark.sql.execution.WholeStageCodegenExec$$anon$1.hasNext(WholeStageCodegenExec.scala:755)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$.$anonfun$executeTask$1(FileFormatWriter.scala:279)
at org.apache.spark.util.Utils$.tryWithSafeFinallyAndFailureCallbacks(Utils.scala:1500)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$.executeTask(FileFormatWriter.scala:288)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$.$anonfun$write$15(FileFormatWriter.scala:212)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)
at org.apache.spark.scheduler.Task.run(Task.scala:131)
at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:497)
at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1466)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:500)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
at java.lang.Thread.run(Thread.java:748)
```
### Does this PR introduce _any_ user-facing change?
No (the legacy config is false by default).
### How was this patch tested?
Added unit tests.
Closes #32501 from fhygh/master.
Authored-by: fhygh <283452027@qq.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
|
||
|---|---|---|
| .. | ||
| catalyst | ||
| core | ||
| hive | ||
| hive-thriftserver | ||
| create-docs.sh | ||
| gen-sql-api-docs.py | ||
| gen-sql-config-docs.py | ||
| gen-sql-functions-docs.py | ||
| mkdocs.yml | ||
| 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.