ODIn/spark-instrumented-optimizer
1
0
Fork 0
Code Issues Pull requests Projects Releases Wiki Activity
spark-instrumented-optimizer/sql
History
Juliusz Sompolski ede35c88e0 [SPARK-26622][SQL] Revise SQL Metrics labels 
## What changes were proposed in this pull request?

Try to make labels more obvious
"avg hash probe"	avg hash probe bucket iterations
"partition pruning time (ms)"	dynamic partition pruning time
"total number of files in the table"	file count
"number of files that would be returned by partition pruning alone"	file count after partition pruning
"total size of files in the table"	file size
"size of files that would be returned by partition pruning alone"	file size after partition pruning
"metadata time (ms)"	metadata time
"aggregate time"	time in aggregation build
"aggregate time"	time in aggregation build
"time to construct rdd bc"	time to build
"total time to remove rows"	time to remove
"total time to update rows"	time to update

Add proper metric type to some metrics:
"bytes of written output"	written output - createSizeMetric
"metadata time"	- createTimingMetric
"dataSize"	- createSizeMetric
"collectTime"	- createTimingMetric
"buildTime"	- createTimingMetric
"broadcastTIme"	- createTimingMetric

## How is this patch tested?

Existing tests.

Author: Stacy Kerkela <stacy.kerkeladatabricks.com>
Signed-off-by: Juliusz Sompolski <julekdatabricks.com>

Closes #23551 from juliuszsompolski/SPARK-26622.

Lead-authored-by: Juliusz Sompolski <julek@databricks.com>
Co-authored-by: Stacy Kerkela <stacy.kerkela@databricks.com>
Signed-off-by: gatorsmile <gatorsmile@gmail.com>
2019-01-17 10:49:42 -08:00
..
catalyst [SPARK-26621][CORE] Use ConfigEntry for hardcoded configs for shuffle categories. 2019-01-17 12:29:17 -06:00
core [SPARK-26622][SQL] Revise SQL Metrics labels 2019-01-17 10:49:42 -08:00
hive [SPARK-23817][SQL] Create file source V2 framework and migrate ORC read path 2019-01-17 23:33:29 +08:00
hive-thriftserver [SPARK-26482][CORE] Use ConfigEntry for hardcoded configs for ui categories 2019-01-11 10:18:07 -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.