c291bd2745
## What changes were proposed in this pull request? In RewriteDistinctAggregates rewrite funtion,after the UDAF's childs are mapped to AttributeRefference, If the UDAF(such as ApproximatePercentile) has a foldable TypeCheck for the input, It will failed because the AttributeRefference is not foldable,then the UDAF is not resolved, and then nullify on the unresolved object will throw a Exception. In this PR, only map Unfoldable child to AttributeRefference, this can avoid the UDAF's foldable TypeCheck. and then only Expand Unfoldable child, there is no need to Expand a static value(foldable value). **Before sql result** > select percentile_approxy(key,0.99999),count(distinct key),sume(distinc key) from src limit 1 > org.apache.spark.sql.catalyst.analysis.UnresolvedException: Invalid call to dataType on unresolved object, tree: 'percentile_approx(CAST(src.`key` AS DOUBLE), CAST(0.99999BD AS DOUBLE), 10000) > at org.apache.spark.sql.catalyst.analysis.UnresolvedAttribute.dataType(unresolved.scala:92) > at org.apache.spark.sql.catalyst.optimizer.RewriteDistinctAggregates$.org$apache$spark$sql$catalyst$optimizer$RewriteDistinctAggregates$$nullify(RewriteDistinctAggregates.scala:261) **After sql result** > select percentile_approxy(key,0.99999),count(distinct key),sume(distinc key) from src limit 1 > [498.0,309,79136] ## How was this patch tested? Add a test case in HiveUDFSuit. Author: root <root@iZbp1gsnrlfzjxh82cz80vZ.(none)> Closes #15668 from windpiger/RewriteDistinctUDAFUnresolveExcep. |
||
|---|---|---|
| .. | ||
| catalyst | ||
| core | ||
| hive | ||
| hive-thriftserver | ||
| 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 an extension of SQLContext called HiveContext that allows users to write queries using a subset of HiveQL and access data from a Hive Metastore using Hive SerDes. There are also wrappers that allows 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.