999d3b89b6
### What changes were proposed in this pull request? Skip null value during rewrite `InSet` to `>= and <=` at getPartitionsByFilter. ### Why are the changes needed? Spark will convert `InSet` to `>= and <=` if it's values size over `spark.sql.hive.metastorePartitionPruningInSetThreshold` during pruning partition . At this case, if values contain a null, we will get such exception ``` java.lang.NullPointerException at org.apache.spark.unsafe.types.UTF8String.compareTo(UTF8String.java:1389) at org.apache.spark.unsafe.types.UTF8String.compareTo(UTF8String.java:50) at scala.math.LowPriorityOrderingImplicits$$anon$3.compare(Ordering.scala:153) at java.util.TimSort.countRunAndMakeAscending(TimSort.java:355) at java.util.TimSort.sort(TimSort.java:220) at java.util.Arrays.sort(Arrays.java:1438) at scala.collection.SeqLike.sorted(SeqLike.scala:659) at scala.collection.SeqLike.sorted$(SeqLike.scala:647) at scala.collection.AbstractSeq.sorted(Seq.scala:45) at org.apache.spark.sql.hive.client.Shim_v0_13.convert$1(HiveShim.scala:772) at org.apache.spark.sql.hive.client.Shim_v0_13.$anonfun$convertFilters$4(HiveShim.scala:826) at scala.collection.immutable.Stream.flatMap(Stream.scala:489) at org.apache.spark.sql.hive.client.Shim_v0_13.convertFilters(HiveShim.scala:826) at org.apache.spark.sql.hive.client.Shim_v0_13.getPartitionsByFilter(HiveShim.scala:848) at org.apache.spark.sql.hive.client.HiveClientImpl.$anonfun$getPartitionsByFilter$1(HiveClientImpl.scala:750) ``` ### Does this PR introduce _any_ user-facing change? Yes, bug fix. ### How was this patch tested? Add test. Closes #31632 from ulysses-you/SPARK-34515. Authored-by: ulysses-you <ulyssesyou18@gmail.com> Signed-off-by: Wenchen Fan <wenchen@databricks.com> |
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.. | ||
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.