#general
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#random
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#feat-compound-types
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#feat-text-search
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#feat-rt-seg-complete
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#feat-presto-connector
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#feat-upsert
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#pinot-helix
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#group-by-refactor
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#qps-metric
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#order-by
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#feat-better-schema-evolution
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#fraud
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#pinotadls
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#inconsistent-segment
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#pinot-power-bi
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#apa-16824
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#pinot-website
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#minion-star-tree
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#troubleshooting
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@ryan.ariasruane: Hi everyone. New here and I was just wanting to ask some questions on ingesting arrays, that is `INT_ARRAY`, `FLOAT_ARRAY`, `TIMESTAMP_ARRAY`, etc. I have found that I can ingest using JSON all types as multi-valued dimension columns with the exception of `BOOLEAN`, `TIMESTAMP`, and `BYTES`. I believe that `JSON_ARRAY` isn't a valid type, but I wasn't sure about `BYTES_ARRAY`. If anyone is about and can shed some light, I would be very appreciative. More info present in-thread
@ryan.ariasruane: For BYTES_ARRAY I get: ```java.lang.UnsupportedOperationException: Unsupported data type : BYTES``` For BOOLEAN_ARRAY I get: ```java.lang.ClassCastException: class [Z cannot be cast to class java.lang.Integer ([Z and java.lang.Integer are in module java.base of loader 'bootstrap')``` For TIMESTAMP_ARRAY I get: ```java.lang.ClassCastException: class java.sql.Timestamp cannot be cast to class java.lang.Long (java.sql.Timestamp is in module java.sql of loader 'platform'; java.lang.Long is in module java.base of loader 'bootstrap')``` So far I have in my docker contained pinot DB a table with all other types in singular and multi-valued form. The schema for the failing types are: ``` "dimensionFieldSpecs": [ { "name": "gamesWon", "dataType": "BOOLEAN", "singleValueField": false }, { "name": "datesPlayed", "dataType": "TIMESTAMP", "singleValueField": false }, { "name": "rawArray", "dataType": "BYTES", "singleValueField": false }``` and the ingestion lines for these columns are: row 1 ``` "datesPlayed": ["2020-01-01 10:45:28", "2020-02-01 10:45:28", "2020-03-01 10:45:28"], "gamesWon": [true, false, true], "rawArray": ["cd", "ef"]``` row 2 ``` "datesPlayed":[] , "gamesWon": [], "rawArray": []```
@ryan.ariasruane: I have also tried ingestion of `TIMESTAMP_ARRAY` as long-typed epoch values, but it makes no difference.
@ryan.ariasruane: Oh, and I'm using the `org.apache.pinot.plugin.inputformat.json.JSONRecordReader`
@mayanks: @ryan.ariasruane do you mind creating an issue for this?
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@taohu: Hi everyone. I updated to 0.10.0 and tried a group by query with filter clause in aggregations but got the following error: ```GROUP BY with FILTER clauses is not supported``` Do we have any plans to support FILTER clause with group by? And for now is there any workaround if I want to filter my aggregations in a group by query? Thanks
@mayanks: @atri.sharma ^^
@atri.sharma: Yep, I am on it.
@atri.sharma: Expect a patch next week. Of course I will send you my crowd funding account number :wink:
@taohu: Awesome, thank you!
@atri.sharma: I was just kidding about the crowd funding account :P let me get a patch out asap
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#pinot-s3
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#pinot-k8s-operator
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#onboarding
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#feat-geo-spatial-index
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#transform-functions
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#custom-aggregators
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#inconsistent-perf
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#docs
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#aggregators
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#query-latency
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#dhill-date-seg
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#enable-generic-offsets
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#pinot-dev
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#community
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#feat-pravega-connector
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#announcements
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#s3-multiple-buckets
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#release-certifier
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#multiple_streams
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#lp-pinot-poc
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#roadmap
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#presto-pinot-connector
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#multi-region-setup
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#metadata-push-api
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#pql-sql-regression
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#latency-during-segment-commit
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#pinot-realtime-table-rebalance
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#release060
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#time-based-segment-pruner
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#discuss-validation
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#segment-cold-storage
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#new-office-space
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#config-tuner
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#test-channel
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#pinot-perf-tuning
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#thirdeye-pinot
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#getting-started
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#feat-partial-upsert
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#pinot_website_improvement_suggestions
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#segment-write-api
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#releases
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#metrics-plugin-impl
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#debug_upsert
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#flink-pinot-connector
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#pinot-rack-awareness
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#minion-improvements
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#fix-numerical-predicate
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#complex-type-support
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#fix_llc_segment_upload
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#product-launch
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#pinot-docsrus
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#pinot-trino
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#kinesis_help
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#udf-type-matching
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#jobs
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#introductions
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#linen_dev
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