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Wenchen Fan c0ae6bc6ea [SPARK-17361][SQL] file-based external table without path should not be created 
## What changes were proposed in this pull request?

Using the public `Catalog` API, users can create a file-based data source table, without giving the path options. For this case, currently we can create the table successfully, but fail when we read it. Ideally we should fail during creation.

This is because when we create data source table, we resolve the data source relation without validating path: `resolveRelation(checkPathExist = false)`.

Looking back to why we add this trick(`checkPathExist`), it's because when we call `resolveRelation` for managed table, we add the path to data source options but the path is not created yet. So why we add this not-yet-created path to data source options? This PR fix the problem by adding path to options after we call `resolveRelation`. Then we can remove the `checkPathExist` parameter in `DataSource.resolveRelation` and do some related cleanups.

## How was this patch tested?

existing tests and new test in `CatalogSuite`

Author: Wenchen Fan <wenchen@databricks.com>

Closes #14921 from cloud-fan/check-path.
2016-09-06 14:17:47 +08:00
..
catalyst [SPARK-17361][SQL] file-based external table without path should not be created 2016-09-06 14:17:47 +08:00
core [SPARK-17361][SQL] file-based external table without path should not be created 2016-09-06 14:17:47 +08:00
hive [SPARK-17361][SQL] file-based external table without path should not be created 2016-09-06 14:17:47 +08:00
hive-thriftserver [SPARK-17190][SQL] Removal of HiveSharedState 2016-08-25 12:50:03 +08:00
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.