wuchong opened a new pull request #14708:
URL: https://github.com/apache/flink/pull/14708
<!--
*Thank you very much for contributing to Apache Flink - we are happy that
you want to help us improve Flink. To help the community review your
contribution in the best possible way, please go through the checklist below,
which will get the contribution into a shape in which it can be best reviewed.*
*Please understand that we do not do this to make contributions to Flink a
hassle. In order to uphold a high standard of quality for code contributions,
while at the same time managing a large number of contributions, we need
contributors to prepare the contributions well, and give reviewers enough
contextual information for the review. Please also understand that
contributions that do not follow this guide will take longer to review and thus
typically be picked up with lower priority by the community.*
## Contribution Checklist
- Make sure that the pull request corresponds to a [JIRA
issue](https://issues.apache.org/jira/projects/FLINK/issues). Exceptions are
made for typos in JavaDoc or documentation files, which need no JIRA issue.
- Name the pull request in the form "[FLINK-XXXX] [component] Title of the
pull request", where *FLINK-XXXX* should be replaced by the actual issue
number. Skip *component* if you are unsure about which is the best component.
Typo fixes that have no associated JIRA issue should be named following
this pattern: `[hotfix] [docs] Fix typo in event time introduction` or
`[hotfix] [javadocs] Expand JavaDoc for PuncuatedWatermarkGenerator`.
- Fill out the template below to describe the changes contributed by the
pull request. That will give reviewers the context they need to do the review.
- Make sure that the change passes the automated tests, i.e., `mvn clean
verify` passes. You can set up Azure Pipelines CI to do that following [this
guide](https://cwiki.apache.org/confluence/display/FLINK/Azure+Pipelines#AzurePipelines-Tutorial:SettingupAzurePipelinesforaforkoftheFlinkrepository).
- Each pull request should address only one issue, not mix up code from
multiple issues.
- Each commit in the pull request has a meaningful commit message
(including the JIRA id)
- Once all items of the checklist are addressed, remove the above text and
this checklist, leaving only the filled out template below.
**(The sections below can be removed for hotfixes of typos)**
-->
## What is the purpose of the change
We have supported cumulative windows in FLINK-19605. However, the current
cumulative window is not efficient, because the slices are not shared.
We leverages the slicing ideas proposed in FLINK-7001 and this design doc
[1]. The slicing is an optimized implementation for hopping, cumulative,
tumbling windows. Besides of that, we introduced ManagedMemory based mini-batch
optimization for the slicing window aggregate operator, this can tremendously
reduce the accessing of state and get the higher throughtput without latency
loss.
[1]:
https://docs.google.com/document/d/1ziVsuW_HQnvJr_4a9yKwx_LEnhVkdlde2Z5l6sx5HlY/edit#
## Brief change log
For slicing window abstraction:
- Introduced a basic `SlicingWindowOperator` to support slicing window
operators, for aggregate and topn in the future.
- Introduce the abstraction of `SliceAssigner` and several implementations,
e.g. tumbling, hopping, cumulative.
For window aggregate operators:
- Introduce the abstraction of `WindowBuffer` to support different
strategies to buffer data. Currently we only support buffering raw records
using `WindowBytesMultiMap`. In the future, we will support buffering
accumulators using `WindowBytesHashMap`.
- Introduce the abstraction of `WindowCombineFunction` to support different
strategies to combine buffered data into state. Currently we only support
combine and accumulate raw records into state. In the future, we will support
combine accumulators into state.
- Implements `SliceSharedWindowAggProcessor` which aggregates data based on
shared slices.
- Implements `SliceUnsharedWindowAggProcessor` which aggregates data based
on unshared slices.
- A `SlicingWindowAggOperatorBuilder` for fluently build a window aggregate
operator.
## Verifying this change
- Added unit tests for every SliceAssigners for every methods
- Added unit tests for tumbling, hopping, cumulative windows for event-time
and processing-time modes.
## Does this pull request potentially affect one of the following parts:
- Dependencies (does it add or upgrade a dependency): (yes / **no**)
- The public API, i.e., is any changed class annotated with
`@Public(Evolving)`: (yes / **no**)
- The serializers: (yes / **no** / don't know)
- The runtime per-record code paths (performance sensitive): (**yes** / no
/ don't know)
- Anything that affects deployment or recovery: JobManager (and its
components), Checkpointing, Yarn/Mesos, ZooKeeper: (yes / **no** / don't know)
- The S3 file system connector: (yes / **no** / don't know)
## Documentation
- Does this pull request introduce a new feature? (yes / **no**)
- If yes, how is the feature documented? (**not applicable** / docs /
JavaDocs / not documented)
----------------------------------------------------------------
This is an automated message from the Apache Git Service.
To respond to the message, please log on to GitHub and use the
URL above to go to the specific comment.
For queries about this service, please contact Infrastructure at:
us...@infra.apache.org
