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## What changes were proposed in this pull request? This patch graduates a list of Spark SQL APIs and mark them stable. The following are marked stable: Dataset/DataFrame - functions, since 1.3 - ColumnName, since 1.3 - DataFrameNaFunctions, since 1.3.1 - DataFrameStatFunctions, since 1.4 - UserDefinedFunction, since 1.3 - UserDefinedAggregateFunction, since 1.5 - Window and WindowSpec, since 1.4 Data sources: - DataSourceRegister, since 1.5 - RelationProvider, since 1.3 - SchemaRelationProvider, since 1.3 - CreatableRelationProvider, since 1.3 - BaseRelation, since 1.3 - TableScan, since 1.3 - PrunedScan, since 1.3 - PrunedFilteredScan, since 1.3 - InsertableRelation, since 1.3 The following are kept experimental / evolving: Data sources: - CatalystScan (tied to internal logical plans so it is not stable by definition) Structured streaming: - all classes (introduced new in 2.0 and will likely change) Dataset typed operations (introduced in 1.6 and 2.0 and might change, although probability is low) - all typed methods on Dataset - KeyValueGroupedDataset - o.a.s.sql.expressions.javalang.typed - o.a.s.sql.expressions.scalalang.typed - methods that return typed Dataset in SparkSession We should discuss more whether we want to mark Dataset typed operations stable in 2.1. ## How was this patch tested? N/A - just annotation changes. Author: Reynold Xin <rxin@databricks.com> Closes #15469 from rxin/SPARK-17900. |
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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.