spark-instrumented-optimizer/sql
Li Zhang dfd7b026dc [SPARK-35800][SS] Improving GroupState testability by introducing TestGroupState
### What changes were proposed in this pull request?
Proposed changes in this pull request:

1. Introducing the `TestGroupState` interface which is inherited from `GroupState` so that testing related getters can be exposed in a controlled manner
2. Changing `GroupStateImpl` to inherit from `TestGroupState` interface, instead of directly from `GroupState`
3. Implementing `TestGroupState` object with `create()` method to forward inputs to the private `GroupStateImpl` constructor
4. User input validations have been added into `GroupStateImpl`'s `createForStreaming()` method to prevent users from creating invalid GroupState objects.
5. Replacing existing `GroupStateImpl` usages in sql pkg internal unit tests with the newly added `TestGroupState` to give user best practice about `TestGroupState` usage.

With the changes in this PR, the class hierarchy is changed from `GroupStateImpl` -> `GroupState` to `GroupStateImpl` -> `TestGroupState` -> `GroupState` (-> means inherits from)

### Why are the changes needed?
The internal `GroupStateImpl` implementation for the `GroupState` interface has no public constructors accessible outside of the sql pkg. However, the user-provided state transition function for `[map|flatMap]GroupsWithState` requires a `GroupState` object as the prevState input.

Currently, users are calling the Structured Streaming engine in their unit tests in order to instantiate such `GroupState` instances, which makes UTs cumbersome.

The proposed `TestGroupState` interface is to give users controlled access to the `GroupStateImpl` internal implementation to largely improve testability of Structured Streaming state transition functions.

**Usage Example**
```
import org.apache.spark.sql.streaming.TestGroupState

test(“Structured Streaming state update function”) {
  var prevState = TestGroupState.create[UserStatus](
    optionalState = Optional.empty[UserStatus],
    timeoutConf = EventTimeTimeout,
    batchProcessingTimeMs = 1L,
    eventTimeWatermarkMs = Optional.of(1L),
    hasTimedOut = false)

  val userId: String = ...
  val actions: Iterator[UserAction] = ...

  assert(!prevState.hasUpdated)

  updateState(userId, actions, prevState)

  assert(prevState.hasUpdated)
}
```

### Does this PR introduce _any_ user-facing change?
Yes, the `TestGroupState` interface and its corresponding `create()` factory function in its companion object are introduced in this pull request for users to use in unit tests.

### How was this patch tested?
- New unit tests are added
- Existing GroupState unit tests are updated

Closes #32938 from lizhangdatabricks/improve-group-state-testability.

Authored-by: Li Zhang <li.zhang@databricks.com>
Signed-off-by: Tathagata Das <tathagata.das1565@gmail.com>
2021-06-22 15:04:01 -04:00
..
catalyst [SPARK-35854][SQL] Improve the error message of to_timestamp_ntz with invalid format pattern 2021-06-22 23:45:54 +08:00
core [SPARK-35800][SS] Improving GroupState testability by introducing TestGroupState 2021-06-22 15:04:01 -04:00
hive [SPARK-35700][SQL] Read char/varchar orc table with created and written by external systems 2021-06-21 19:20:55 -07:00
hive-thriftserver [SPARK-35838][BUILD][TESTS] Ensure all modules can be maven test independently in Scala 2.13 2021-06-22 06:31:24 -07:00
create-docs.sh [SPARK-34010][SQL][DODCS] Use python3 instead of python in SQL documentation build 2021-01-05 19:48:10 +09:00
gen-sql-api-docs.py [SPARK-34747][SQL][DOCS] Add virtual operators to the built-in function document 2021-03-19 10:19:26 +09:00
gen-sql-config-docs.py [SPARK-32194][PYTHON] Use proper exception classes instead of plain Exception 2021-05-26 11:54:40 +09:00
gen-sql-functions-docs.py [SPARK-31562][SQL] Update ExpressionDescription for substring, current_date, and current_timestamp 2020-04-26 11:46:52 -07:00
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.