Implement a generic aggregation transform step #2076
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dominiklohmann
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Awesome to see the Arrow Compute API being leveraged! |
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dominiklohmann
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Feb 10, 2022
dominiklohmann
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Feb 10, 2022
dominiklohmann
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mavam
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dominiklohmann
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dispanser
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Fine with me! Made a minor comment, also assuming you're going to repair the build 🗡️
Digging through the arrow APIs, I found https://arrow.apache.org/docs/dev/cpp/compute.html#grouped-aggregations-group-by which may one day become an off-the-shelf way to do this without explicitly handling the grouping ourselves.
Great to see that generic and powerful aggregation plugin 👍
@dispanser the main issue is that this only supports grouping on a single column, which is insufficient for our use cases. |
mavam
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Feb 14, 2022
mavam
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Feb 14, 2022
This implements a generic aggregation transform step plugin. E.g., to configure
it for flow aggregation on export, the following may be used:
```yaml
vast:
transforms:
suricata-flow-aggregate:
- aggregate:
time-window: 10 seconds
group-by:
- timestamp
- src_ip
- dest_ip
- dest_port
- proto
- event_type
sum:
- pcap_cnt
- flow.pkts_toserver
- flow.pkts_toclient
- flow.bytes_toserver
- flow.bytes_toclient
min:
- flow.start
max:
- flow.end
any:
- flow.alerted
# all:
layout-name: suricata.aggregated_flow
- replace:
field: event_type
value: aggregated_flow
transform-triggers:
export:
- transform: suricata-flow-aggregate
location: client
events:
- suricata.flow
- suricata.aggregated_flow
```
This is a rewrite of the aggregate transform step and its underlying algorithm to have two passes, each of which can be disabled: An eager pass when adding record batches, and a lazy pass when retrieving the results. Additionally, it refactors the per-layout aggregation into a separate data structure that is easier to maintain, and adds explanatory comments throughout the file.
This fixes some minor issues in the aggregate plugin noticed during a review session.
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This implements a generic aggregation transform step plugin. See the attached README file for more information.
📝 Checklist
🎯 Review Instructions
File-by-file. Go over the algorithm in a call with me. Test locally alongside compaction.