a4ea599b1b
### What changes were proposed in this pull request? A unit test is added Partition duplicate check added in `org.apache.spark.sql.execution.datasources.PartitioningUtils#validatePartitionColumn` ### Why are the changes needed? When people write data with duplicate partition column, it will cause a `org.apache.spark.sql.AnalysisException: Found duplicate column ...` in loading data from the writted. ### Does this PR introduce _any_ user-facing change? Yes. It will prevent people from using duplicate partition columns to write data. 1. Before the PR: It will look ok at `df.write.partitionBy("b", "b").csv("file:///tmp/output")`, but get an exception when read: `spark.read.csv("file:///tmp/output").show()` org.apache.spark.sql.AnalysisException: Found duplicate column(s) in the partition schema: `b`; 2. After the PR: `df.write.partitionBy("b", "b").csv("file:///tmp/output")` will trigger the exception: org.apache.spark.sql.AnalysisException: Found duplicate column(s) b, b: `b`; ### How was this patch tested? Unit test. Closes #28814 from TJX2014/master-SPARK-31968. Authored-by: TJX2014 <xiaoxingstack@gmail.com> Signed-off-by: Dongjoon Hyun <dongjoon@apache.org> |
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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.