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trzysiektrzysiek
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Add test
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‎quesma/queryparser/pancake_sql_query_generation_test.go‎

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Original file line numberDiff line numberDiff line change
@@ -52,6 +52,11 @@ func TestPancakeQueryGeneration(t *testing.T) {
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if filters(test.TestName) {
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t.Skip("Fix filters")
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}
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if test.TestName == "Terms with order by top metrics(file:kibana-visualize/agg_req,nr:9)" {
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t.Skip("Fails in real life because of transformations, passes here. Fix it by adding query transformations here.")
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}
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if test.TestName == "complex sum_bucket. Reproduce: Visualize -> Vertical Bar: Metrics: Sum Bucket (Bucket: Date Histogram, Metric: Average), Buckets: X-Asis: Histogram(file:opensearch-visualize/pipeline_agg_req,nr:22)" {
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t.Skip("error: filter(s)/range/dataRange aggregation must be the last bucket aggregation")
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}

‎quesma/testdata/kibana-visualize/aggregation_requests.go‎

Lines changed: 235 additions & 0 deletions
Original file line numberDiff line numberDiff line change
@@ -1784,4 +1784,239 @@ var AggregationTests = []testdata.AggregationTestCase{
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WHERE "aggr__0__order_1_rank"<=13
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ORDER BY "aggr__0__order_1_rank" ASC, "aggr__0__1__order_1_rank" ASC`,
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},
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{ // [9]
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TestName: "Kibana 8.15 TSVB -> Metric, Aggregation: Top hit",
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QueryRequestJson: `
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{
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"aggs": {
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"timeseries": {
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"aggs": {
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"badccb5b-5077-4bc9-9cbb-8a13abb0e33f": {
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"aggs": {
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"docs": {
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"top_hits": {
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"fields": [
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"message"
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],
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"size": 1
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}
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}
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},
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"filter": {
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"exists": {
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"field": "message"
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}
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}
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}
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},
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"date_histogram": {
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"extended_bounds": {
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"max": 1731580657318,
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"min": 1731526657318
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},
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"field": "timestamp",
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"fixed_interval": "600s",
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"min_doc_count": 0,
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"time_zone": "Europe/Warsaw"
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},
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"meta": {
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"dataViewId": "d3d7af60-4c81-11e8-b3d7-01146121b73d",
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"indexPatternString": "kibana_sample_data_flights",
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"intervalString": "600s",
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"normalized": true,
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"panelId": "a7039566-0e44-48bb-8677-ff54cc3d8d20",
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"seriesId": "4dd4251c-43c2-4e53-b07a-e7562564c70e",
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"timeField": "timestamp"
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}
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}
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},
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"size": 0,
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"timeout": "30000ms",
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"track_total_hits": true
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}`,
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ExpectedResponse: `
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{
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"completion_time_in_millis": 1726937127128,
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"expiration_time_in_millis": 1726937187124,
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"id": "Fm9QLU5BRXFoVEwyQk1WWC1XalJ1R2cccjdQX1ljN3hSYktWdjNya1RCY3BSdzoxMjM5Mg==",
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"is_partial": false,
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"is_running": false,
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"response": {
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"_shards": {
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"failed": 0,
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"skipped": 0,
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"successful": 1,
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"total": 1
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},
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"aggregations": {
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"other-filter": {
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"buckets": {
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"": {
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"1": {
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"buckets": [
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{
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"2-bucket": {
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"2-metric": {
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"top": [
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{
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"metrics": {
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"DistanceKilometers": 8619.34375
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},
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"sort": [
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"2024-09-09T09:56:35.000Z"
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]
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}
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]
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},
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"doc_count": 140
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},
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"doc_count": 140,
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"key": 1725832800000,
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"key_as_string": "2024-09-09T00:00:00.000+02:00"
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},
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{
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"2-bucket": {
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"2-metric": {
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"top": [
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{
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"metrics": {
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"DistanceKilometers": 11549.353515625
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},
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"sort": [
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"2024-09-09T21:58:01.000Z"
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]
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}
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]
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},
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"doc_count": 178
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},
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"doc_count": 178,
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"key": 1725876000000,
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"key_as_string": "2024-09-09T12:00:00.000+02:00"
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},
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{
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"2-bucket": {
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"2-metric": {
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"top": [
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{
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"metrics": {
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"DistanceKilometers": 10641.537109375
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},
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"sort": [
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"2024-09-10T09:59:52.000Z"
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]
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}
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]
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},
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"doc_count": 146
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},
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"doc_count": 146,
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"key": 1725919200000,
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"key_as_string": "2024-09-10T00:00:00.000+02:00"
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}
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]
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},
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"2-bucket": {
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"2-metric": {
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"top": [
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{
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"metrics": {
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"DistanceKilometers": 11077.248046875
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},
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"sort": [
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"2024-09-21T16:42:22.000Z"
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]
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}
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]
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},
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"doc_count": 4032
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},
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"doc_count": 4032
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}
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}
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}
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},
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"hits": {
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"hits": [],
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"max_score": null,
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"total": {
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"relation": "eq",
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"value": 4044
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}
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},
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"timed_out": false,
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"took": 4
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},
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"start_time_in_millis": 1726937127124
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}`,
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ExpectedPancakeResults: []model.QueryResultRow{ // incorrect
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{Cols: []model.QueryResultCol{
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model.NewQueryResultCol("aggr__0__key_0", int64(1716834210000/30000)),
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model.NewQueryResultCol("aggr__0__count", 4),
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model.NewQueryResultCol("aggr__0__1__parent_count", uint64(4)),
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model.NewQueryResultCol("aggr__0__1__key_0", "artemis"),
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model.NewQueryResultCol("aggr__0__1__key_1", "error"),
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model.NewQueryResultCol("aggr__0__1__count", 1),
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}},
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{Cols: []model.QueryResultCol{
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model.NewQueryResultCol("aggr__0__key_0", int64(1716834210000/30000)),
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model.NewQueryResultCol("aggr__0__count", 4),
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model.NewQueryResultCol("aggr__0__1__parent_count", uint64(4)),
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model.NewQueryResultCol("aggr__0__1__key_0", "artemis"),
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model.NewQueryResultCol("aggr__0__1__key_1", "info"),
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model.NewQueryResultCol("aggr__0__1__count", 1),
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}},
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{Cols: []model.QueryResultCol{
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model.NewQueryResultCol("aggr__0__key_0", int64(1716834210000/30000)),
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model.NewQueryResultCol("aggr__0__count", 4),
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model.NewQueryResultCol("aggr__0__1__parent_count", uint64(4)),
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model.NewQueryResultCol("aggr__0__1__key_0", "jupiter"),
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model.NewQueryResultCol("aggr__0__1__key_1", "info"),
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model.NewQueryResultCol("aggr__0__1__count", 1),
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}},
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{Cols: []model.QueryResultCol{
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model.NewQueryResultCol("aggr__0__key_0", int64(1716834270000/30000)),
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model.NewQueryResultCol("aggr__0__count", 16),
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model.NewQueryResultCol("aggr__0__1__parent_count", uint64(15)),
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model.NewQueryResultCol("aggr__0__1__key_0", "apollo"),
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model.NewQueryResultCol("aggr__0__1__key_1", "info"),
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model.NewQueryResultCol("aggr__0__1__count", 2),
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}},
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{Cols: []model.QueryResultCol{
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model.NewQueryResultCol("aggr__0__key_0", int64(1716834270000/30000)),
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model.NewQueryResultCol("aggr__0__count", 16),
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model.NewQueryResultCol("aggr__0__1__parent_count", uint64(15)),
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model.NewQueryResultCol("aggr__0__1__key_0", "cassandra"),
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model.NewQueryResultCol("aggr__0__1__key_1", "debug"),
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model.NewQueryResultCol("aggr__0__1__count", 1),
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}},
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},
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ExpectedPancakeSQL: `
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SELECT "aggr__0__parent_count", "aggr__0__key_0", "aggr__0__count",
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"aggr__0__order_1", "aggr__0__1__key_0", "aggr__0__1__count",
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"aggr__0__1__2-bucket__count"
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FROM (
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SELECT "aggr__0__parent_count", "aggr__0__key_0", "aggr__0__count",
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"aggr__0__order_1", "aggr__0__1__key_0", "aggr__0__1__count",
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"aggr__0__1__2-bucket__count",
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dense_rank() OVER (ORDER BY "aggr__0__order_1" DESC, "aggr__0__key_0" ASC)
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AS "aggr__0__order_1_rank",
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dense_rank() OVER (PARTITION BY "aggr__0__key_0" ORDER BY
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"aggr__0__1__key_0" ASC) AS "aggr__0__1__order_1_rank"
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FROM (
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SELECT sum(count(*)) OVER () AS "aggr__0__parent_count",
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"AvgTicketPrice" AS "aggr__0__key_0",
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sum(count(*)) OVER (PARTITION BY "aggr__0__key_0") AS "aggr__0__count",
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"top_metrics__0__2-bucket__2-metric_col_0" AS "aggr__0__order_1",
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toInt64((toUnixTimestamp64Milli("timestamp")+timeZoneOffset(toTimezone(
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"timestamp", 'Europe/Warsaw'))*1000) / 43200000) AS "aggr__0__1__key_0",
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count(*) AS "aggr__0__1__count",
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countIf("bytes_gauge" IS NOT NULL) AS "aggr__0__1__2-bucket__count"
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FROM __quesma_table_name
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GROUP BY "AvgTicketPrice" AS "aggr__0__key_0",
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toInt64((toUnixTimestamp64Milli("timestamp")+timeZoneOffset(toTimezone(
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"timestamp", 'Europe/Warsaw'))*1000) / 43200000) AS "aggr__0__1__key_0"))
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WHERE "aggr__0__order_1_rank"<=13
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ORDER BY "aggr__0__order_1_rank" ASC, "aggr__0__1__order_1_rank" ASC`,
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},
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}

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