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## What changes were proposed in this pull request? Metrics are needed for monitoring structured streaming apps. Here is the design doc for implementing the necessary metrics. https://docs.google.com/document/d/1NIdcGuR1B3WIe8t7VxLrt58TJB4DtipWEbj5I_mzJys/edit?usp=sharing Specifically, this PR adds the following public APIs changes. ### New APIs - `StreamingQuery.status` returns a `StreamingQueryStatus` object (renamed from `StreamingQueryInfo`, see later) - `StreamingQueryStatus` has the following important fields - inputRate - Current rate (rows/sec) at which data is being generated by all the sources - processingRate - Current rate (rows/sec) at which the query is processing data from all the sources - ~~outputRate~~ - *Does not work with wholestage codegen* - latency - Current average latency between the data being available in source and the sink writing the corresponding output - sourceStatuses: Array[SourceStatus] - Current statuses of the sources - sinkStatus: SinkStatus - Current status of the sink - triggerStatus - Low-level detailed status of the last completed/currently active trigger - latencies - getOffset, getBatch, full trigger, wal writes - timestamps - trigger start, finish, after getOffset, after getBatch - numRows - input, output, state total/updated rows for aggregations - `SourceStatus` has the following important fields - inputRate - Current rate (rows/sec) at which data is being generated by the source - processingRate - Current rate (rows/sec) at which the query is processing data from the source - triggerStatus - Low-level detailed status of the last completed/currently active trigger - Python API for `StreamingQuery.status()` ### Breaking changes to existing APIs **Existing direct public facing APIs** - Deprecated direct public-facing APIs `StreamingQuery.sourceStatuses` and `StreamingQuery.sinkStatus` in favour of `StreamingQuery.status.sourceStatuses/sinkStatus`. - Branch 2.0 should have it deprecated, master should have it removed. **Existing advanced listener APIs** - `StreamingQueryInfo` renamed to `StreamingQueryStatus` for consistency with `SourceStatus`, `SinkStatus` - Earlier StreamingQueryInfo was used only in the advanced listener API, but now it is used in direct public-facing API (StreamingQuery.status) - Field `queryInfo` in listener events `QueryStarted`, `QueryProgress`, `QueryTerminated` changed have name `queryStatus` and return type `StreamingQueryStatus`. - Field `offsetDesc` in `SourceStatus` was Option[String], converted it to `String`. - For `SourceStatus` and `SinkStatus` made constructor private instead of private[sql] to make them more java-safe. Instead added `private[sql] object SourceStatus/SinkStatus.apply()` which are harder to accidentally use in Java. ## How was this patch tested? Old and new unit tests. - Rate calculation and other internal logic of StreamMetrics tested by StreamMetricsSuite. - New info in statuses returned through StreamingQueryListener is tested in StreamingQueryListenerSuite. - New and old info returned through StreamingQuery.status is tested in StreamingQuerySuite. - Source-specific tests for making sure input rows are counted are is source-specific test suites. - Additional tests to test minor additions in LocalTableScanExec, StateStore, etc. Metrics also manually tested using Ganglia sink Author: Tathagata Das <tathagata.das1565@gmail.com> Closes #15307 from tdas/SPARK-17731. |
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| 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.