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Kent Yao 8c6748f691 [SPARK-34817][SQL] Read parquet unsigned types that stored as int32 physical type in parquet 
### What changes were proposed in this pull request?

Unsigned types may be used to produce smaller in-memory representations of the data. These types used by frameworks(e.g. hive, pig) using parquet. And parquet will map them to its base types.

see more https://github.com/apache/parquet-format/blob/master/LogicalTypes.md
https://github.com/apache/parquet-format/blob/master/src/main/thrift/parquet.thrift

```thrift
  /**
   * An unsigned integer value.
   *
   * The number describes the maximum number of meaningful data bits in
   * the stored value. 8, 16 and 32 bit values are stored using the
   * INT32 physical type.  64 bit values are stored using the INT64
   * physical type.
   *
   */
  UINT_8 = 11;
  UINT_16 = 12;
  UINT_32 = 13;
  UINT_64 = 14;
```

```
UInt8-[0:255]
UInt16-[0:65535]
UInt32-[0:4294967295]
UInt64-[0:18446744073709551615]
```

In this PR, we support read UINT_8 as ShortType, UINT_16 as IntegerType, UINT_32 as LongType to fit their range. Support for UINT_64 will be in another PR.

### Why are the changes needed?

better parquet support

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

yes, we can read unit[8/16/32] from parquet files

### How was this patch tested?

new tests

Closes #31921 from yaooqinn/SPARK-34817.

Authored-by: Kent Yao <yao@apache.org>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
2021-03-25 06:58:06 +00:00
..
catalyst [SPARK-34701][SQL] Remove analyzing temp view again in CreateViewCommand 2021-03-25 06:53:59 +00:00
core [SPARK-34817][SQL] Read parquet unsigned types that stored as int32 physical type in parquet 2021-03-25 06:58:06 +00:00
hive [SPARK-34852][SQL] Close Hive session state should use withHiveState 2021-03-25 10:21:44 +08:00
hive-thriftserver [SPARK-34700][SQL] SessionCatalog's temporary view related APIs should take/return more concrete types 2021-03-22 08:17:54 +00:00
create-docs.sh [SPARK-34010][SQL][DODCS] Use python3 instead of python in SQL documentation build 2021-01-05 19:48:10 +09:00
gen-sql-api-docs.py [SPARK-34747][SQL][DOCS] Add virtual operators to the built-in function document 2021-03-19 10:19:26 +09:00
gen-sql-config-docs.py [SPARK-31550][SQL][DOCS] Set nondeterministic configurations with general meanings in sql configuration doc 2020-04-27 17:08:52 +09:00
gen-sql-functions-docs.py [SPARK-31562][SQL] Update ExpressionDescription for substring, current_date, and current_timestamp 2020-04-26 11:46:52 -07:00
mkdocs.yml [SPARK-30731] Update deprecated Mkdocs option 2020-02-19 17:28:58 +09:00
README.md [SPARK-30510][SQL][DOCS] Publicly document Spark SQL configuration options 2020-02-09 19:20:47 +09:00

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 extensions that allow users to write queries using a subset of HiveQL and access data from a Hive Metastore using Hive SerDes. There are also wrappers that allow 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.

Running ./sql/create-docs.sh generates SQL documentation for built-in functions under sql/site, and SQL configuration documentation that gets included as part of configuration.md in the main docs directory.