spark-instrumented-optimizer/sql
Jungtaek Lim (HeartSaVioR) 39bc50dbf8 [SPARK-30804][SS] Measure and log elapsed time for "compact" operation in CompactibleFileStreamLog
### What changes were proposed in this pull request?

This patch adds some log messages to log elapsed time for "compact" operation in FileStreamSourceLog and FileStreamSinkLog (added in CompactibleFileStreamLog) to help investigating the mysterious latency spike during the batch run.

### Why are the changes needed?

Tracking latency is a critical aspect of streaming query. While "compact" operation may bring nontrivial latency (it's even synchronous, adding all the latency to the batch run), it's not measured and end users have to guess.

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

No.

### How was this patch tested?

N/A for UT. Manual test with streaming query using file source & file sink.

> grep "for compact batch" <driver log>

```
...
20/02/20 19:27:36 WARN FileStreamSinkLog: Compacting took 24473 ms (load: 14185 ms, write: 10288 ms) for compact batch 21359
20/02/20 19:27:39 WARN FileStreamSinkLog: Loaded 1068000 entries (397985432 bytes in memory), and wrote 1068000 entries for compact batch 21359
20/02/20 19:29:52 WARN FileStreamSourceLog: Compacting took 3777 ms (load: 1524 ms, write: 2253 ms) for compact batch 21369
20/02/20 19:29:52 WARN FileStreamSourceLog: Loaded 229477 entries (68970112 bytes in memory), and wrote 229477 entries for compact batch 21369
20/02/20 19:30:17 WARN FileStreamSinkLog: Compacting took 24183 ms (load: 12992 ms, write: 11191 ms) for compact batch 21369
20/02/20 19:30:20 WARN FileStreamSinkLog: Loaded 1068500 entries (398171880 bytes in memory), and wrote 1068500 entries for compact batch 21369
...
```

![Screen Shot 2020-02-21 at 12 34 22 PM](https://user-images.githubusercontent.com/1317309/75002142-c6830100-54a6-11ea-8da6-17afb056653b.png)

This messages are explaining why the operation duration peaks per every 10 batches which is compact interval. Latency from addBatch heavily increases in each peak which DOES NOT mean it takes more time to write outputs, but we have no idea if such message is not presented.

NOTE: The output may be a bit different from the code, as it may be changed a bit during review phase.

Closes #27557 from HeartSaVioR/SPARK-30804.

Authored-by: Jungtaek Lim (HeartSaVioR) <kabhwan.opensource@gmail.com>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
2020-04-24 12:34:44 +09:00
..
catalyst [SPARK-31488][SQL] Support java.time.LocalDate in Parquet filter pushdown 2020-04-24 02:21:53 +00:00
core [SPARK-30804][SS] Measure and log elapsed time for "compact" operation in CompactibleFileStreamLog 2020-04-24 12:34:44 +09:00
hive [SPARK-31522][SQL] Hive metastore client initialization related configurations should be static 2020-04-23 15:07:44 +00:00
hive-thriftserver [SPARK-31381][SPARK-29245][SQL] Upgrade built-in Hive 2.3.6 to 2.3.7 2020-04-20 13:38:24 -07:00
create-docs.sh [SPARK-31498][SQL][DOCS] Dump public static sql configurations through doc generation 2020-04-22 10:16:39 +00:00
gen-sql-api-docs.py [SPARK-31474][SQL][FOLLOWUP] Replace _FUNC_ placeholder with functionname in the note field of expression info 2020-04-23 13:33:04 +09:00
gen-sql-config-docs.py [SPARK-31498][SQL][DOCS] Dump public static sql configurations through doc generation 2020-04-22 10:16:39 +00:00
gen-sql-functions-docs.py [SPARK-31429][SQL][DOC] Automatically generates a SQL document for built-in functions 2020-04-21 10:55:13 +09:00
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

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.