[SPARK-31709][SQL] Proper base path for database/table location when it is a relative path

### What changes were proposed in this pull request?

Currently, the user home directory is used as the base path for the database and table locations when their locationa are specified with a relative paths, e.g.
```sql
> set spark.sql.warehouse.dir;
spark.sql.warehouse.dir	file:/Users/kentyao/Downloads/spark/spark-3.1.0-SNAPSHOT-bin-20200512/spark-warehouse/
spark-sql> create database loctest location 'loctestdbdir';

spark-sql> desc database loctest;
Database Name	loctest
Comment
Location	file:/Users/kentyao/Downloads/spark/spark-3.1.0-SNAPSHOT-bin-20200512/loctestdbdir
Owner	kentyao

spark-sql> create table loctest(id int) location 'loctestdbdir';
spark-sql> desc formatted loctest;
id	int	NULL

# Detailed Table Information
Database	default
Table	loctest
Owner	kentyao
Created Time	Thu May 14 16:29:05 CST 2020
Last Access	UNKNOWN
Created By	Spark 3.1.0-SNAPSHOT
Type	EXTERNAL
Provider	parquet
Location	file:/Users/kentyao/Downloads/spark/spark-3.1.0-SNAPSHOT-bin-20200512/loctestdbdir
Serde Library	org.apache.hadoop.hive.ql.io.parquet.serde.ParquetHiveSerDe
InputFormat	org.apache.hadoop.hive.ql.io.parquet.MapredParquetInputFormat
OutputFormat	org.apache.hadoop.hive.ql.io.parquet.MapredParquetOutputFormat
```
The user home is not always warehouse-related, unchangeable in runtime, and shared both by database and table as the parent directory. Meanwhile, we use the table path as the parent directory for relative partition locations.

The config `spark.sql.warehouse.dir` represents `the default location for managed databases and tables`.
For databases, the case above seems not to follow its semantics, because it should use ` `spark.sql.warehouse.dir` as the base path instead.

For tables, it seems to be right but here I suggest enriching the meaning that lets it also be the for external tables with relative paths for locations.

With changes in this PR,

The location of a database will be `warehouseDir/dbpath` when `dbpath` is relative.
The location of a table will be `dbpath/tblpath` when `tblpath` is relative.

### Why are the changes needed?

bugfix and improvement

Firstly, the databases with relative locations should be created under the default location specified by `spark.sql.warehouse.dir`.

Secondly, the external tables with relative paths may also follow this behavior for consistency.

At last, the behavior for database, tables and partitions with relative paths to choose base paths should be the same.

### Does this PR introduce _any_ user-facing change?

Yes, this PR changes the `createDatabase`, `alterDatabase`, `createTable` and `alterTable` APIs and related DDLs. If the LOCATION clause is followed by a relative path, the root path will be `spark.sql.warehouse.dir` for databases, and `spark.sql.warehouse.dir` / `dbPath` for tables.

e.g.

#### after
```sql
spark-sql> desc database loctest;
Database Name	loctest
Comment
Location	file:/Users/kentyao/Downloads/spark/spark-3.1.0-SNAPSHOT-bin-SPARK-31709/spark-warehouse/loctest
Owner	kentyao
spark-sql> use loctest;
spark-sql> create table loctest(id int) location 'loctest';
20/05/14 18:18:02 WARN InMemoryFileIndex: The directory file:/Users/kentyao/Downloads/spark/spark-3.1.0-SNAPSHOT-bin-SPARK-31709/loctest was not found. Was it deleted very recently?
20/05/14 18:18:02 WARN SessionState: METASTORE_FILTER_HOOK will be ignored, since hive.security.authorization.manager is set to instance of HiveAuthorizerFactory.
20/05/14 18:18:03 WARN HiveConf: HiveConf of name hive.internal.ss.authz.settings.applied.marker does not exist
20/05/14 18:18:03 WARN HiveConf: HiveConf of name hive.stats.jdbc.timeout does not exist
20/05/14 18:18:03 WARN HiveConf: HiveConf of name hive.stats.retries.wait does not exist
spark-sql> desc formatted loctest;
id	int	NULL

# Detailed Table Information
Database	loctest
Table	loctest
Owner	kentyao
Created Time	Thu May 14 18:18:03 CST 2020
Last Access	UNKNOWN
Created By	Spark 3.1.0-SNAPSHOT
Type	EXTERNAL
Provider	parquet
Location	file:/Users/kentyao/Downloads/spark/spark-3.1.0-SNAPSHOT-bin-SPARK-31709/spark-warehouse/loctest/loctest
Serde Library	org.apache.hadoop.hive.ql.io.parquet.serde.ParquetHiveSerDe
InputFormat	org.apache.hadoop.hive.ql.io.parquet.MapredParquetInputFormat
OutputFormat	org.apache.hadoop.hive.ql.io.parquet.MapredParquetOutputFormat
spark-sql> alter table loctest set location 'loctest2'
         > ;
spark-sql> desc formatted loctest;
id	int	NULL

# Detailed Table Information
Database	loctest
Table	loctest
Owner	kentyao
Created Time	Thu May 14 18:18:03 CST 2020
Last Access	UNKNOWN
Created By	Spark 3.1.0-SNAPSHOT
Type	EXTERNAL
Provider	parquet
Location	file:/Users/kentyao/Downloads/spark/spark-3.1.0-SNAPSHOT-bin-SPARK-31709/spark-warehouse/loctest/loctest2
Serde Library	org.apache.hadoop.hive.ql.io.parquet.serde.ParquetHiveSerDe
InputFormat	org.apache.hadoop.hive.ql.io.parquet.MapredParquetInputFormat
OutputFormat	org.apache.hadoop.hive.ql.io.parquet.MapredParquetOutputFormat
```
### How was this patch tested?

Add unit tests.

Closes #28527 from yaooqinn/SPARK-31709.

Authored-by: Kent Yao <yaooqinn@hotmail.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
3 files changed
tree: f9b456227bb534c56ccff7e5907656e8d257bdc9
  1. .github/
  2. assembly/
  3. bin/
  4. build/
  5. common/
  6. conf/
  7. core/
  8. data/
  9. dev/
  10. docs/
  11. examples/
  12. external/
  13. graphx/
  14. hadoop-cloud/
  15. launcher/
  16. licenses/
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  18. mllib/
  19. mllib-local/
  20. project/
  21. python/
  22. R/
  23. repl/
  24. resource-managers/
  25. sbin/
  26. sql/
  27. streaming/
  28. tools/
  29. .asf.yaml
  30. .gitattributes
  31. .gitignore
  32. appveyor.yml
  33. CONTRIBUTING.md
  34. LICENSE
  35. LICENSE-binary
  36. NOTICE
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  38. pom.xml
  39. README.md
  40. scalastyle-config.xml
README.md

Apache Spark

Spark is a unified analytics engine for large-scale data processing. It provides high-level APIs in Scala, Java, Python, and R, and an optimized engine that supports general computation graphs for data analysis. It also supports a rich set of higher-level tools including Spark SQL for SQL and DataFrames, MLlib for machine learning, GraphX for graph processing, and Structured Streaming for stream processing.

https://spark.apache.org/

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You can find the latest Spark documentation, including a programming guide, on the project web page. This README file only contains basic setup instructions.

Building Spark

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./build/mvn -DskipTests clean package

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More detailed documentation is available from the project site, at “Building Spark”.

For general development tips, including info on developing Spark using an IDE, see “Useful Developer Tools”.

Interactive Scala Shell

The easiest way to start using Spark is through the Scala shell:

./bin/spark-shell

Try the following command, which should return 1,000,000,000:

scala> spark.range(1000 * 1000 * 1000).count()

Interactive Python Shell

Alternatively, if you prefer Python, you can use the Python shell:

./bin/pyspark

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>>> spark.range(1000 * 1000 * 1000).count()

Example Programs

Spark also comes with several sample programs in the examples directory. To run one of them, use ./bin/run-example <class> [params]. For example:

./bin/run-example SparkPi

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MASTER=spark://host:7077 ./bin/run-example SparkPi

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Please see the guidance on how to run tests for a module, or individual tests.

There is also a Kubernetes integration test, see resource-managers/kubernetes/integration-tests/README.md

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