f643fe47f4
Revise HDFSMetadataLog API such that metadata object serialization and final batch file write are separated. This will allow serialization checks without worrying about batch file name formats. marmbrus zsxwing Existing tests already ensure this API faithfully support core functionality i.e., creation of batch files. Author: Tyson Condie <tcondie@gmail.com> Closes #15924 from tcondie/SPARK-18498. Signed-off-by: Michael Armbrust <michael@databricks.com> |
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catalyst | ||
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hive | ||
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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.