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test: show stats in explain of two representative queries #8173

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86 changes: 85 additions & 1 deletion datafusion/sqllogictest/test_files/explain.slt
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Original file line number Diff line number Diff line change
Expand Up @@ -279,13 +279,97 @@ physical_plan
GlobalLimitExec: skip=0, fetch=10, statistics=[Rows=Inexact(10), Bytes=Absent, [(Col[0]:),(Col[1]:),(Col[2]:)]]
--CsvExec: file_groups={1 group: [[WORKSPACE_ROOT/datafusion/core/tests/data/example.csv]]}, projection=[a, b, c], limit=10, has_header=true, statistics=[Rows=Absent, Bytes=Absent, [(Col[0]:),(Col[1]:),(Col[2]:)]]

# Parquet scan with statistics collected
# Collect statistics
statement ok
set datafusion.execution.collect_statistics = true;

# CSV scan
# query having almost presentative opererators
query TT
explain
SELECT t1.c1, sum(t2.c4)
FROM aggregate_test_100_with_order as t1, aggregate_test_100_with_order as t2
WHERE t1.c3 > 10 and t1.c11 != 30.5
AND t2.c13 = 'whatever'
AND t1.c2 = t2.c2 and t2.c10 < 987654321
GROUP BY t1.c1
HAVING sum(t2.c4) > 1
ORDER BY t1.c1 ASC
LIMIT 10;
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@alamb : At first I thought I would add many small queries and on single data type but it turns out, if I do so, I have to add quite many and also many combinations for different data types. Still, they do not cover the propagation I want to see. Thus, I have to add complicated queries plus those small queries.

To avoid that, I decided to go with 2 quite representative queries, one on CVS file and one on parquet file. Each I have different combinations of filters on different data types and includes common standard SQL clauses (select, from, where, group by, having, order by, limit). They not only show the statistics for each operator but also how they are propagated upward.

Let me know what you think. I am happy to add small queries, too

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I think this makes sense and is a great first step.

----
physical_plan
GlobalLimitExec: skip=0, fetch=10, statistics=[Rows=Inexact(10), Bytes=Absent, [(Col[0]:),(Col[1]:)]]
--SortPreservingMergeExec: [c1@0 ASC NULLS LAST], fetch=10, statistics=[Rows=Absent, Bytes=Absent, [(Col[0]: Min=Exact(Utf8(NULL)) Max=Exact(Utf8(NULL))),(Col[1]: Min=Inexact(Int64(2)) Max=Inexact(Int64(NULL)))]]
----SortExec: TopK(fetch=10), expr=[c1@0 ASC NULLS LAST], statistics=[Rows=Absent, Bytes=Absent, [(Col[0]: Min=Exact(Utf8(NULL)) Max=Exact(Utf8(NULL))),(Col[1]: Min=Inexact(Int64(2)) Max=Inexact(Int64(NULL)))]]
------CoalesceBatchesExec: target_batch_size=8192, statistics=[Rows=Absent, Bytes=Absent, [(Col[0]: Min=Exact(Utf8(NULL)) Max=Exact(Utf8(NULL))),(Col[1]: Min=Inexact(Int64(2)) Max=Inexact(Int64(NULL)))]]
--------FilterExec: SUM(t2.c4)@1 > 1, statistics=[Rows=Absent, Bytes=Absent, [(Col[0]: Min=Exact(Utf8(NULL)) Max=Exact(Utf8(NULL))),(Col[1]: Min=Inexact(Int64(2)) Max=Inexact(Int64(NULL)))]]
----------AggregateExec: mode=FinalPartitioned, gby=[c1@0 as c1], aggr=[SUM(t2.c4)], statistics=[Rows=Absent, Bytes=Absent, [(Col[0]:),(Col[1]:)]]
------------CoalesceBatchesExec: target_batch_size=8192, statistics=[Rows=Absent, Bytes=Absent, [(Col[0]:),(Col[1]:)]]
--------------RepartitionExec: partitioning=Hash([c1@0], 4), input_partitions=4, statistics=[Rows=Absent, Bytes=Absent, [(Col[0]:),(Col[1]:)]]
----------------AggregateExec: mode=Partial, gby=[c1@0 as c1], aggr=[SUM(t2.c4)], statistics=[Rows=Absent, Bytes=Absent, [(Col[0]:),(Col[1]:)]]
------------------ProjectionExec: expr=[c1@0 as c1, c4@3 as c4], statistics=[Rows=Absent, Bytes=Absent, [(Col[0]:),(Col[1]:)]]
--------------------CoalesceBatchesExec: target_batch_size=8192, statistics=[Rows=Absent, Bytes=Absent, [(Col[0]:),(Col[1]:),(Col[2]:),(Col[3]:)]]
----------------------HashJoinExec: mode=Partitioned, join_type=Inner, on=[(c2@1, c2@0)], statistics=[Rows=Absent, Bytes=Absent, [(Col[0]:),(Col[1]:),(Col[2]:),(Col[3]:)]]
------------------------CoalesceBatchesExec: target_batch_size=8192, statistics=[Rows=Absent, Bytes=Absent, [(Col[0]:),(Col[1]:)]]
--------------------------RepartitionExec: partitioning=Hash([c2@1], 4), input_partitions=4, statistics=[Rows=Absent, Bytes=Absent, [(Col[0]:),(Col[1]:)]]
----------------------------ProjectionExec: expr=[c1@0 as c1, c2@1 as c2], statistics=[Rows=Absent, Bytes=Absent, [(Col[0]:),(Col[1]:)]]
------------------------------CoalesceBatchesExec: target_batch_size=8192, statistics=[Rows=Absent, Bytes=Absent, [(Col[0]:),(Col[1]:),(Col[2]:),(Col[3]:)]]
--------------------------------FilterExec: c3@2 > 10 AND CAST(c11@3 AS Float64) != 30.5, statistics=[Rows=Absent, Bytes=Absent, [(Col[0]:),(Col[1]:),(Col[2]:),(Col[3]:)]]
----------------------------------RepartitionExec: partitioning=RoundRobinBatch(4), input_partitions=1, statistics=[Rows=Absent, Bytes=Absent, [(Col[0]:),(Col[1]:),(Col[2]:),(Col[3]:)]]
------------------------------------CsvExec: file_groups={1 group: [[WORKSPACE_ROOT/datafusion/core/tests/data/aggregate_test_100_order_by_c1_asc.csv]]}, projection=[c1, c2, c3, c11], output_ordering=[c1@0 ASC NULLS LAST], has_header=true, statistics=[Rows=Absent, Bytes=Absent, [(Col[0]:),(Col[1]:),(Col[2]:),(Col[3]:)]]
------------------------CoalesceBatchesExec: target_batch_size=8192, statistics=[Rows=Absent, Bytes=Absent, [(Col[0]:),(Col[1]:)]]
--------------------------RepartitionExec: partitioning=Hash([c2@0], 4), input_partitions=4, statistics=[Rows=Absent, Bytes=Absent, [(Col[0]:),(Col[1]:)]]
----------------------------ProjectionExec: expr=[c2@0 as c2, c4@1 as c4], statistics=[Rows=Absent, Bytes=Absent, [(Col[0]:),(Col[1]:)]]
------------------------------CoalesceBatchesExec: target_batch_size=8192, statistics=[Rows=Absent, Bytes=Absent, [(Col[0]:),(Col[1]:),(Col[2]:),(Col[3]:)]]
--------------------------------FilterExec: c13@3 = whatever AND c10@2 < 987654321, statistics=[Rows=Absent, Bytes=Absent, [(Col[0]:),(Col[1]:),(Col[2]:),(Col[3]:)]]
----------------------------------RepartitionExec: partitioning=RoundRobinBatch(4), input_partitions=1, statistics=[Rows=Absent, Bytes=Absent, [(Col[0]:),(Col[1]:),(Col[2]:),(Col[3]:)]]
------------------------------------CsvExec: file_groups={1 group: [[WORKSPACE_ROOT/datafusion/core/tests/data/aggregate_test_100_order_by_c1_asc.csv]]}, projection=[c2, c4, c10, c13], has_header=true, statistics=[Rows=Absent, Bytes=Absent, [(Col[0]:),(Col[1]:),(Col[2]:),(Col[3]:)]]


# ################################################
# Parquet
statement ok
CREATE EXTERNAL TABLE alltypes_plain STORED AS PARQUET LOCATION '../../parquet-testing/data/alltypes_plain.parquet';


# Parquet scan
# query having almost presentative opererators
query TT
explain
SELECT t1.date_string_col, max(t2.timestamp_col)
FROM alltypes_plain as t1, alltypes_plain as t2
WHERE t1.bool_col = true AND t1.string_col != 'whatever'
AND t2.double_col < 10.1
AND t1.id = t2.id
GROUP BY t1.date_string_col
HAVING max(t2.timestamp_col) < '2010-01-01'
ORDER BY t1.date_string_col ASC
LIMIT 10;
----
physical_plan
GlobalLimitExec: skip=0, fetch=10, statistics=[Rows=Inexact(10), Bytes=Absent, [(Col[0]:),(Col[1]:)]]
--SortPreservingMergeExec: [date_string_col@0 ASC NULLS LAST], fetch=10, statistics=[Rows=Absent, Bytes=Absent, [(Col[0]:),(Col[1]:)]]
----SortExec: TopK(fetch=10), expr=[date_string_col@0 ASC NULLS LAST], statistics=[Rows=Absent, Bytes=Absent, [(Col[0]:),(Col[1]:)]]
------CoalesceBatchesExec: target_batch_size=8192, statistics=[Rows=Absent, Bytes=Absent, [(Col[0]:),(Col[1]:)]]
--------FilterExec: MAX(t2.timestamp_col)@1 < 1262304000000000000, statistics=[Rows=Absent, Bytes=Absent, [(Col[0]:),(Col[1]:)]]
----------AggregateExec: mode=FinalPartitioned, gby=[date_string_col@0 as date_string_col], aggr=[MAX(t2.timestamp_col)], statistics=[Rows=Absent, Bytes=Absent, [(Col[0]:),(Col[1]:)]]
------------CoalesceBatchesExec: target_batch_size=8192, statistics=[Rows=Absent, Bytes=Absent, [(Col[0]:),(Col[1]:)]]
--------------RepartitionExec: partitioning=Hash([date_string_col@0], 4), input_partitions=4, statistics=[Rows=Absent, Bytes=Absent, [(Col[0]:),(Col[1]:)]]
----------------AggregateExec: mode=Partial, gby=[date_string_col@0 as date_string_col], aggr=[MAX(t2.timestamp_col)], statistics=[Rows=Absent, Bytes=Absent, [(Col[0]:),(Col[1]:)]]
------------------ProjectionExec: expr=[date_string_col@1 as date_string_col, timestamp_col@3 as timestamp_col], statistics=[Rows=Absent, Bytes=Absent, [(Col[0]:),(Col[1]:)]]
--------------------CoalesceBatchesExec: target_batch_size=8192, statistics=[Rows=Absent, Bytes=Absent, [(Col[0]:),(Col[1]:),(Col[2]:),(Col[3]:)]]
----------------------HashJoinExec: mode=CollectLeft, join_type=Inner, on=[(id@0, id@0)], statistics=[Rows=Absent, Bytes=Absent, [(Col[0]:),(Col[1]:),(Col[2]:),(Col[3]:)]]
------------------------ProjectionExec: expr=[id@0 as id, date_string_col@2 as date_string_col], statistics=[Rows=Inexact(1), Bytes=Absent, [(Col[0]:),(Col[1]:)]]
--------------------------CoalesceBatchesExec: target_batch_size=8192, statistics=[Rows=Inexact(1), Bytes=Absent, [(Col[0]:),(Col[1]:),(Col[2]:),(Col[3]:)]]
----------------------------FilterExec: bool_col@1 AND string_col@3 != 119,104,97,116,101,118,101,114, statistics=[Rows=Inexact(1), Bytes=Absent, [(Col[0]:),(Col[1]:),(Col[2]:),(Col[3]:)]]
------------------------------ParquetExec: file_groups={1 group: [[WORKSPACE_ROOT/parquet-testing/data/alltypes_plain.parquet]]}, projection=[id, bool_col, date_string_col, string_col], predicate=bool_col@1 AND string_col@9 != 119,104,97,116,101,118,101,114, pruning_predicate=(bool_col_min@0 OR bool_col_max@1) AND (string_col_min@2 != 119,104,97,116,101,118,101,114 OR 119,104,97,116,101,118,101,114 != string_col_max@3), statistics=[Rows=Exact(8), Bytes=Absent, [(Col[0]:),(Col[1]:),(Col[2]:),(Col[3]:)]]
------------------------RepartitionExec: partitioning=RoundRobinBatch(4), input_partitions=1, statistics=[Rows=Inexact(8), Bytes=Absent, [(Col[0]: Min=Exact(Int32(NULL)) Max=Exact(Int32(NULL))),(Col[1]: Min=Exact(TimestampNanosecond(NULL, None)) Max=Exact(TimestampNanosecond(NULL, None)))]]
--------------------------ProjectionExec: expr=[id@0 as id, timestamp_col@2 as timestamp_col], statistics=[Rows=Inexact(8), Bytes=Absent, [(Col[0]: Min=Exact(Int32(NULL)) Max=Exact(Int32(NULL))),(Col[1]: Min=Exact(TimestampNanosecond(NULL, None)) Max=Exact(TimestampNanosecond(NULL, None)))]]
----------------------------CoalesceBatchesExec: target_batch_size=8192, statistics=[Rows=Inexact(8), Bytes=Absent, [(Col[0]: Min=Exact(Int32(NULL)) Max=Exact(Int32(NULL))),(Col[1]: Min=Inexact(Float64(NULL)) Max=Inexact(Float64(10.099999999999998))),(Col[2]: Min=Exact(TimestampNanosecond(NULL, None)) Max=Exact(TimestampNanosecond(NULL, None)))]]
------------------------------FilterExec: double_col@1 < 10.1, statistics=[Rows=Inexact(8), Bytes=Absent, [(Col[0]: Min=Exact(Int32(NULL)) Max=Exact(Int32(NULL))),(Col[1]: Min=Inexact(Float64(NULL)) Max=Inexact(Float64(10.099999999999998))),(Col[2]: Min=Exact(TimestampNanosecond(NULL, None)) Max=Exact(TimestampNanosecond(NULL, None)))]]
--------------------------------ParquetExec: file_groups={1 group: [[WORKSPACE_ROOT/parquet-testing/data/alltypes_plain.parquet]]}, projection=[id, double_col, timestamp_col], predicate=double_col@7 < 10.1, pruning_predicate=double_col_min@0 < 10.1, statistics=[Rows=Exact(8), Bytes=Absent, [(Col[0]:),(Col[1]:),(Col[2]:)]]


query TT
EXPLAIN SELECT * FROM alltypes_plain limit 10;
----
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