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Gengliang Wang b90bfe3c42 [SPARK-24771][BUILD] Upgrade Apache AVRO to 1.8.2 
## What changes were proposed in this pull request?

Upgrade Apache Avro from 1.7.7 to 1.8.2. The major new features:

1. More logical types. From the spec of 1.8.2 https://avro.apache.org/docs/1.8.2/spec.html#Logical+Types we can see comparing to [1.7.7](https://avro.apache.org/docs/1.7.7/spec.html#Logical+Types), the new version support:
    - Date
    - Time (millisecond precision)
    - Time (microsecond precision)
    - Timestamp (millisecond precision)
    - Timestamp (microsecond precision)
    - Duration

2. Single-object encoding: https://avro.apache.org/docs/1.8.2/spec.html#single_object_encoding

This PR aims to update Apache Spark to support these new features.

## How was this patch tested?

Unit test

Author: Gengliang Wang <gengliang.wang@databricks.com>

Closes #21761 from gengliangwang/upgrade_avro_1.8.
2018-07-30 07:30:47 -07:00
..
catalyst [SPARK-24957][SQL] Average with decimal followed by aggregation returns wrong result 2018-07-30 20:53:45 +08:00
core [SPARK-24771][BUILD] Upgrade Apache AVRO to 1.8.2 2018-07-30 07:30:47 -07:00
hive [SPARK-24957][SQL] Average with decimal followed by aggregation returns wrong result 2018-07-30 20:53:45 +08:00
hive-thriftserver [SPARK-24829][STS] In Spark Thrift Server, CAST AS FLOAT inconsistent with spark-shell or spark-sql 2018-07-27 13:27:17 +08:00
create-docs.sh [MINOR][DOCS] Minor doc fixes related with doc build and uses script dir in SQL doc gen script 2017-08-26 13:56:24 +09:00
gen-sql-markdown.py [SPARK-21485][FOLLOWUP][SQL][DOCS] Describes examples and arguments separately, and note/since in SQL built-in function documentation 2017-08-05 10:10:56 -07:00
mkdocs.yml [SPARK-21485][SQL][DOCS] Spark SQL documentation generation for built-in functions 2017-07-26 09:38:51 -07:00
README.md [MINOR][DOC] Fix some typos and grammar issues 2018-04-06 13:37:08 +08:00

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 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.