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VinceShieh 0b076d4cb6 [SPARK-17219][ML] enhanced NaN value handling in Bucketizer 
## What changes were proposed in this pull request?

This PR is an enhancement of PR with commit ID:57dc326bd00cf0a49da971e9c573c48ae28acaa2.
NaN is a special type of value which is commonly seen as invalid. But We find that there are certain cases where NaN are also valuable, thus need special handling. We provided user when dealing NaN values with 3 options, to either reserve an extra bucket for NaN values, or remove the NaN values, or report an error, by setting handleNaN "keep", "skip", or "error"(default) respectively.

'''Before:
val bucketizer: Bucketizer = new Bucketizer()
          .setInputCol("feature")
          .setOutputCol("result")
          .setSplits(splits)
'''After:
val bucketizer: Bucketizer = new Bucketizer()
          .setInputCol("feature")
          .setOutputCol("result")
          .setSplits(splits)
          .setHandleNaN("keep")

## How was this patch tested?
Tests added in QuantileDiscretizerSuite, BucketizerSuite and DataFrameStatSuite

Signed-off-by: VinceShieh <vincent.xieintel.com>

Author: VinceShieh <vincent.xie@intel.com>
Author: Vincent Xie <vincent.xie@intel.com>
Author: Joseph K. Bradley <joseph@databricks.com>

Closes #15428 from VinceShieh/spark-17219_followup.
2016-10-27 11:52:15 -07:00
..
catalyst [SPARK-17770][CATALYST] making ObjectType public 2016-10-26 18:03:31 -07:00
core [SPARK-17219][ML] enhanced NaN value handling in Bucketizer 2016-10-27 11:52:15 -07:00
hive [SPARK-18026][SQL] should not always lowercase partition columns of partition spec in parser 2016-10-25 15:00:33 +08:00
hive-thriftserver [SPARK-17819][SQL] Support default database in connection URIs for Spark Thrift Server 2016-10-16 20:15:32 -07:00
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.