spark-instrumented-optimizer/sql
Takeshi YAMAMURO 5585ed93b0 [SPARK-17237][SQL] Remove backticks in a pivot result schema
## 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.
2017-01-12 09:46:53 -08:00
..
catalyst [SPARK-17237][SQL] Remove backticks in a pivot result schema 2017-01-12 09:46:53 -08:00
core [SPARK-17237][SQL] Remove backticks in a pivot result schema 2017-01-12 09:46:53 -08:00
hive [SPARK-19183][SQL] Add deleteWithJob hook to internal commit protocol API 2017-01-12 17:45:55 +08:00
hive-thriftserver [SPARK-18857][SQL] Don't use Iterator.duplicate for incrementalCollect in Thrift Server 2017-01-10 13:27:55 +00:00
README.md [SPARK-16557][SQL] Remove stale doc in sql/README.md 2016-07-14 19:24:42 -07:00

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.