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aokolnychyi ca4e960aec [SPARK-17914][SQL] Fix parsing of timestamp strings with nanoseconds 
The PR contains a tiny change to fix the way Spark parses string literals into timestamps. Currently, some timestamps that contain nanoseconds are corrupted during the conversion from internal UTF8Strings into the internal representation of timestamps.

Consider the following example:
```
spark.sql("SELECT cast('2015-01-02 00:00:00.000000001' as TIMESTAMP)").show(false)
+------------------------------------------------+
|CAST(2015-01-02 00:00:00.000000001 AS TIMESTAMP)|
+------------------------------------------------+
|2015-01-02 00:00:00.000001                      |
+------------------------------------------------+
```

The fix was tested with existing tests. Also, there is a new test to cover cases that did not work previously.

Author: aokolnychyi <anton.okolnychyi@sap.com>

Closes #18252 from aokolnychyi/spark-17914.
2017-06-12 13:06:14 -07:00
..
catalyst [SPARK-17914][SQL] Fix parsing of timestamp strings with nanoseconds 2017-06-12 13:06:14 -07:00
core [SPARK-21046][SQL] simplify the array offset and length in ColumnVector 2017-06-13 00:12:34 +08:00
hive [SPARK-21031][SQL] Add alterTableStats to store spark's stats and let alterTable keep existing stats 2017-06-12 08:23:04 +08:00
hive-thriftserver [SPARK-20966][WEB-UI][SQL] Table data is not sorted by startTime time desc, time is not formatted and redundant code in JDBC/ODBC Server page. 2017-06-07 10:18:40 +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.