ODIn/spark-instrumented-optimizer
1
0
Fork 0
Code Issues Pull requests Projects Releases Wiki Activity
spark-instrumented-optimizer/sql
History
uncleGen 3d740901d6 [SPARK-29973][SS] Make processedRowsPerSecond calculated more accurately and meaningfully 
### What changes were proposed in this pull request?

Give `processingTimeSec` 0.001 when a micro-batch completed under 1ms.

### Why are the changes needed?

The `processingTimeSec` of batch may be less than 1 ms.  As `processingTimeSec` is calculated in ms, so `processingTimeSec` equals 0L. If there is no data in this batch, the `processedRowsPerSecond` equals `0/0.0d`, i.e. `Double.NaN`. If there are some data in this batch, the `processedRowsPerSecond` equals `N/0.0d`, i.e. `Double.Infinity`.

### Does this PR introduce any user-facing change?
No

### How was this patch tested?
Add new UT

Closes #26610 from uncleGen/SPARK-29973.

Authored-by: uncleGen <hustyugm@gmail.com>
Signed-off-by: Sean Owen <sean.owen@databricks.com>
2019-11-24 08:08:15 -06:00
..
catalyst [SPARK-29554][SQL][FOLLOWUP] Rename Version to SparkVersion 2019-11-23 19:53:52 -08:00
core [SPARK-29973][SS] Make processedRowsPerSecond calculated more accurately and meaningfully 2019-11-24 08:08:15 -06:00
hive [SPARK-29981][BUILD] Add hive-1.2/2.3 profiles 2019-11-23 10:02:22 -08:00
hive-thriftserver [SPARK-29981][BUILD][FOLLOWUP] Change hive.version.short 2019-11-23 12:50:50 -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-27328][SQL] Add 'deprecated' in ExpressionDescription for extended usage and SQL doc 2019-04-09 13:49:42 +08:00
mkdocs.yml [SPARK-21485][SQL][DOCS] Spark SQL documentation generation for built-in functions 2017-07-26 09:38:51 -07:00
README.md [SPARK-28980][CORE][SQL][STREAMING][MLLIB] Remove most items deprecated in Spark 2.2.0 or earlier, for Spark 3 2019-09-09 10:19:40 -05:00

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.