3ac0382759
### What changes were proposed in this pull request? Change allowed input types of `Abs()` from: ``` NumericType + CalendarIntervalType + YearMonthIntervalType + DayTimeIntervalType ``` to ``` NumericType + YearMonthIntervalType + DayTimeIntervalType ``` ### Why are the changes needed? The changes make the error message more clear. Before changes: ```sql spark-sql> set spark.sql.legacy.interval.enabled=true; spark.sql.legacy.interval.enabled true spark-sql> select abs(interval -10 days -20 minutes); 21/10/05 09:11:30 ERROR SparkSQLDriver: Failed in [select abs(interval -10 days -20 minutes)] java.lang.ClassCastException: org.apache.spark.sql.types.CalendarIntervalType$ cannot be cast to org.apache.spark.sql.types.NumericType at org.apache.spark.sql.catalyst.util.TypeUtils$.getNumeric(TypeUtils.scala:77) at org.apache.spark.sql.catalyst.expressions.Abs.numeric$lzycompute(arithmetic.scala:172) at org.apache.spark.sql.catalyst.expressions.Abs.numeric(arithmetic.scala:169) ``` After: ```sql spark.sql.legacy.interval.enabled true spark-sql> select abs(interval -10 days -20 minutes); Error in query: cannot resolve 'abs(INTERVAL '-10 days -20 minutes')' due to data type mismatch: argument 1 requires (numeric or interval day to second or interval year to month) type, however, 'INTERVAL '-10 days -20 minutes'' is of interval type.; line 1 pos 7; 'Project [unresolvedalias(abs(-10 days -20 minutes, false), None)] +- OneRowRelation ``` ### Does this PR introduce _any_ user-facing change? No, because the original changes of https://github.com/apache/spark/pull/34169 haven't released yet. ### How was this patch tested? Manually checked in the command line, see examples above. Closes #34183 from MaxGekk/fix-abs-input-types. Authored-by: Max Gekk <max.gekk@gmail.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.