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Add time window and window assigner #950
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dai-chen
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opensearch-project:feature/maximus-m1
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dai-chen:maximus-m1/add-window-assigner
Oct 27, 2022
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Add time window and window assigner #950
dai-chen
merged 3 commits into
opensearch-project:feature/maximus-m1
from
dai-chen:maximus-m1/add-window-assigner
Oct 27, 2022
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Signed-off-by: Chen Dai <daichen@amazon.com>
43 tasks
Codecov Report
@@ Coverage Diff @@
## feature/maximus-m1 #950 +/- ##
========================================================
- Coverage 97.95% 95.22% -2.74%
- Complexity 3143 3153 +10
========================================================
Files 300 313 +13
Lines 7784 8463 +679
Branches 500 623 +123
========================================================
+ Hits 7625 8059 +434
- Misses 158 350 +192
- Partials 1 54 +53
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Signed-off-by: Chen Dai <daichen@amazon.com>
dai-chen
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Add window and window assigner
Add time window and window assigner
Oct 21, 2022
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penghuo
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Oct 26, 2022
...ain/java/org/opensearch/sql/planner/streaming/windowing/assigner/TumblingWindowAssigner.java
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...main/java/org/opensearch/sql/planner/streaming/windowing/assigner/SlidingWindowAssigner.java
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Signed-off-by: Chen Dai <daichen@amazon.com>
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Signed-off-by: Chen Dai daichen@amazon.com
Description
Add window and window assigner interface along with tumbling and sliding window assigner implementation. This PR is only focus on core
WindowAssigner
interface. The future tasks in #954 will integrate it and other new windowing components with query plan operator.Window
A Window is a time interval which has start timestamp and end timestamp. For convenience, the end timestamp is exclusive and thus the window boundary is actually
[startTime, endTime-1]
.Window Assigner
A WindowAssigner identifies which window(s) the event belong. This is the first step and foundation of handling unbounded streaming data. As follows, an event may be assigned to a single window or multiple windows according to the windowing function. Here are a few example for common windowing approach.
Tumble window is fixed size without any overlap and start timestamp is aligned by mod window size.
Sliding window is fixed size but overlapped by slide size. The algorithm is referencing https://github.com/apache/flink/blob/master/flink-streaming-java/src/main/java/org/apache/flink/streaming/api/windowing/assigners/SlidingEventTimeWindows.java#L70
Session windowing dynamic sized and defined by a given gap duration. It is useful for event representing user activity by analyzing user behavior within a session. Note that session window may cause window merging which will be supported in future as needed.
Issues Resolved
#951
Check List
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