f4237aff7e
### What changes were proposed in this pull request? This PR fixes an issue that `from_csv/to_csv` doesn't handle year-month intervals properly. `from_csv` throws exception if year-month interval types are given. ``` spark-sql> select from_csv("interval '1-2' year to month", "a interval year to month"); 21/07/03 04:32:24 ERROR SparkSQLDriver: Failed in [select from_csv("interval '1-2' year to month", "a interval year to month")] java.lang.Exception: Unsupported type: interval year to month at org.apache.spark.sql.errors.QueryExecutionErrors$.unsupportedTypeError(QueryExecutionErrors.scala:775) at org.apache.spark.sql.catalyst.csv.UnivocityParser.makeConverter(UnivocityParser.scala:224) at org.apache.spark.sql.catalyst.csv.UnivocityParser.$anonfun$valueConverters$1(UnivocityParser.scala:134) ``` Also, `to_csv` doesn't handle year-month interval types properly though any exception is thrown. The result of `to_csv` for year-month interval types is not ANSI interval compliant form. ``` spark-sql> select to_csv(named_struct("a", interval '1-2' year to month)); 14 ``` The result above should be `INTERVAL '1-2' YEAR TO MONTH`. ### Why are the changes needed? Bug fix. ### Does this PR introduce _any_ user-facing change? No. ### How was this patch tested? New tests. Closes #33210 from sarutak/csv-yminterval. Authored-by: Kousuke Saruta <sarutak@oss.nttdata.com> Signed-off-by: Max Gekk <max.gekk@gmail.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.