b3130c7b6a
## What changes were proposed in this pull request?
This PR proposes to make `DataFrameReader.jdbc` call `DataFrameReader.format("jdbc").load` consistently with other APIs in `DataFrameReader`/`DataFrameWriter` and avoid calling `sparkSession.baseRelationToDataFrame(..)` here and there.
The changes were mostly copied from `DataFrameWriter.jdbc()` which was recently updated.
```diff
- val params = extraOptions.toMap ++ connectionProperties.asScala.toMap
- val options = new JDBCOptions(url, table, params)
- val relation = JDBCRelation(parts, options)(sparkSession)
- sparkSession.baseRelationToDataFrame(relation)
+ this.extraOptions = this.extraOptions ++ connectionProperties.asScala
+ // explicit url and dbtable should override all
+ this.extraOptions += ("url" -> url, "dbtable" -> table)
+ format("jdbc").load()
```
## How was this patch tested?
Existing tests should cover this.
Author: hyukjinkwon <gurwls223@gmail.com>
Closes #15499 from HyukjinKwon/SPARK-17955.
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| hive | ||
| hive-thriftserver | ||
| 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.