5585ed93b0
## What changes were proposed in this pull request? Pivoting adds backticks (e.g. 3_count(\`c\`)) in column names and, in some cases, thes causes analysis exceptions like; ``` scala> val df = Seq((2, 3, 4), (3, 4, 5)).toDF("a", "x", "y") scala> df.groupBy("a").pivot("x").agg(count("y"), avg("y")).na.fill(0) org.apache.spark.sql.AnalysisException: syntax error in attribute name: `3_count(`y`)`; at org.apache.spark.sql.catalyst.analysis.UnresolvedAttribute$.e$1(unresolved.scala:134) at org.apache.spark.sql.catalyst.analysis.UnresolvedAttribute$.parseAttributeName(unresolved.scala:144) ... ``` So, this pr proposes to remove these backticks from column names. ## How was this patch tested? Added a test in `DataFrameAggregateSuite`. Author: Takeshi YAMAMURO <linguin.m.s@gmail.com> Closes #14812 from maropu/SPARK-17237. |
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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.