locationtech / locationtech/geomesa
Implement Spark (+ SQL) count to use datastore count methods
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Description
Implement Spark (+ SQL) count to use datastore count methods
It appears that right now, df.count() is bringing back the results and counting them in spark. We should override this and use our optimized counting (e.g. stats iterator), through the data store API. We should make sure to set the hint to use exact counts.
Possibly this is a regression bug?
Original JIRA Issue: https://geomesa.atlassian.net/browse/GEOMESA-2333
Key: GEOMESA-2333
Type: Improvement
Priority: Major
Status: To Do
Resolution: Unresolved
Reporter: Emilio Lahr-Vivaz
Created: Fri, 20 Jul 2018 10:07:48 -0400
Updated: Fri, 20 Jul 2018 10:10:36 -0400
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start by tracing how Spark SQL implements df.count() and how that path reaches the datastore API. Compare it with the available datastore count methods, including the stats iterator, and verify that the exact-count hint is set and records are not fetched before counting.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- scala, spark, sql
- Domain
- data, distributed-systems
- Issue type
- Feature
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Quiet
- Clarity
- Mostly clear
- Newbie friendliness
- 48/100