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Dongjoon Hyun abff92bfdc [SPARK-16975][SQL] Column-partition path starting '_' should be handled correctly 
## What changes were proposed in this pull request?

Currently, Spark ignores path names starting with underscore `_` and `.`. This causes read-failures for the column-partitioned file data sources whose partition column names starts from '_', e.g. `_col`.

**Before**
```scala
scala> spark.range(10).withColumn("_locality_code", $"id").write.partitionBy("_locality_code").save("/tmp/parquet")
scala> spark.read.parquet("/tmp/parquet")
org.apache.spark.sql.AnalysisException: Unable to infer schema for ParquetFormat at /tmp/parquet20. It must be specified manually;
```

**After**
```scala
scala> spark.range(10).withColumn("_locality_code", $"id").write.partitionBy("_locality_code").save("/tmp/parquet")
scala> spark.read.parquet("/tmp/parquet")
res2: org.apache.spark.sql.DataFrame = [id: bigint, _locality_code: int]
```

## How was this patch tested?

Pass the Jenkins with a new test case.

Author: Dongjoon Hyun <dongjoon@apache.org>

Closes #14585 from dongjoon-hyun/SPARK-16975-PARQUET.
2016-08-12 14:40:12 +08:00
..
catalyst [SPARK-16958] [SQL] Reuse subqueries within the same query 2016-08-11 09:47:19 -07:00
core [SPARK-16975][SQL] Column-partition path starting '_' should be handled correctly 2016-08-12 14:40:12 +08:00
hive [SPARK-16866][SQL] Infrastructure for file-based SQL end-to-end tests 2016-08-10 17:17:21 +08:00
hive-thriftserver [SPARK-16941] Use concurrentHashMap instead of scala Map in SparkSQLOperationManager. 2016-08-11 11:28:28 +01:00
README.md [SPARK-16557][SQL] Remove stale doc in sql/README.md 2016-07-14 19:24:42 -07:00

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.