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Currently just including the local/remote groups which reference materializations, but materializations aren't displayed:
---- EXPLAIN ---- SELECT s_acctbal, s_name, n_name, p_partkey, p_mfgr, s_address, s_phone, s_comment FROM '../submodules/testdata/tpch_sf0.1/part.parquet' part, '../submodules/testdata/tpch_sf0.1/supplier.parquet' supplier, '../submodules/testdata/tpch_sf0.1/partsupp.parquet' partsupp, '../submodules/testdata/tpch_sf0.1/nation.parquet' nation, '../submodules/testdata/tpch_sf0.1/region.parquet' region WHERE p_partkey = ps_partkey AND s_suppkey = ps_suppkey AND p_size = 15 AND p_type LIKE '%BRASS' AND s_nationkey = n_nationkey AND n_regionkey = r_regionkey AND r_name = 'EUROPE' AND ps_supplycost = ( SELECT min(ps_supplycost) FROM '../submodules/testdata/tpch_sf0.1/partsupp.parquet' partsupp, '../submodules/testdata/tpch_sf0.1/supplier.parquet' supplier, '../submodules/testdata/tpch_sf0.1/nation.parquet' nation, '../submodules/testdata/tpch_sf0.1/region.parquet' region WHERE p_partkey = ps_partkey AND s_suppkey = ps_suppkey AND s_nationkey = n_nationkey AND n_regionkey = r_regionkey AND r_name = 'EUROPE') ORDER BY s_acctbal DESC, n_name, s_name, p_partkey LIMIT 100; ┌───────────┬─────────────────────────────────────────────────────────────────────────────────────────────────────────┐ │ plan_type │ plan │ │ Utf8 │ Utf8 │ ├───────────┼─────────────────────────────────────────────────────────────────────────────────────────────────────────┤ │ unoptimi… │ Project (location = Any, projections = [#5.0, GlareDB/glaredb_next#5.1, GlareDB/glaredb_next#5.2, GlareDB/glaredb_next#5.3, GlareDB/glaredb_next#5.4, GlareDB/glaredb_next#5.5, GlareDB/glaredb_next#5.6, GlareDB/glaredb_next#5.7], table_ref = │ │ │ GlareDB/glaredb_next#14) │ │ │ Limit (limit = 100, location = Any) │ │ │ Order (expressions = [#5.8 desc nulls_first, GlareDB/glaredb_next#5.9 asc nulls_first, GlareDB/glaredb_next#5.10 asc nulls_first, GlareDB/glaredb_next#5.11 asc │ │ │ nulls_first], location = Any) │ │ │ Project (location = Any, projections = [#1.5, GlareDB/glaredb_next#1.1, GlareDB/glaredb_next#3.1, #0.0, #0.2, GlareDB/glaredb_next#1.2, GlareDB/glaredb_next#1.4, GlareDB/glaredb_next#1.6, GlareDB/glaredb_next#1.5, │ │ │ GlareDB/glaredb_next#3.1, GlareDB/glaredb_next#1.1, #0.0], table_ref = GlareDB/glaredb_next#5) │ │ │ Filter (location = Any, predicate = #0.0 = GlareDB/glaredb_next#2.0 AND GlareDB/glaredb_next#1.0 = GlareDB/glaredb_next#2.1 AND CAST(#0.5 TO Int64) = 15 │ │ │ AND ends_with(#0.4, '%BRASS') AND GlareDB/glaredb_next#1.3 = GlareDB/glaredb_next#3.0 AND GlareDB/glaredb_next#3.2 = GlareDB/glaredb_next#4.0 AND GlareDB/glaredb_next#4.1 = 'EUROPE' AND GlareDB/glaredb_next#2.3 = GlareDB/glaredb_next#10.0) │ │ │ ComparisonJoin (conditions = [#0.0 = GlareDB/glaredb_next#10.1], join_type = LEFT, location = Any) │ │ │ MaterializationScan (location = Any, materialization_ref = MAT_0, table_refs = [#0, GlareDB/glaredb_next#1, GlareDB/glaredb_next#2, │ │ │ GlareDB/glaredb_next#3, GlareDB/glaredb_next#4]) │ │ │ CrossJoin (location = Any) │ │ │ Scan (column_names = [p_partkey, p_name, p_mfgr, p_brand, p_type, p_size, p_container, │ │ │ p_retailprice, p_comment], column_types = [Int32, Utf8, Utf8, Utf8, Utf8, Int32, Utf8, Decimal64(15,2), │ │ │ Utf8], function_name = read_parquet, location = ClientLocal, projection = [0, 1, 2, 3, 4, 5, 6, 7, 8], │ │ │ table_ref = #0) │ │ │ CrossJoin (location = Any) │ │ │ Scan (column_names = [s_suppkey, s_name, s_address, s_nationkey, s_phone, s_acctbal, │ │ │ s_comment], column_types = [Int32, Utf8, Utf8, Int32, Utf8, Decimal64(15,2), Utf8], function_name = │ │ │ read_parquet, location = ClientLocal, projection = [0, 1, 2, 3, 4, 5, 6], table_ref = GlareDB/glaredb_next#1) │ │ │ CrossJoin (location = Any) │ │ │ Scan (column_names = [ps_partkey, ps_suppkey, ps_availqty, ps_supplycost, │ │ │ ps_comment], column_types = [Int32, Int32, Int32, Decimal64(15,2), Utf8], function_name = read_parquet, │ │ │ location = ClientLocal, projection = [0, 1, 2, 3, 4], table_ref = GlareDB/glaredb_next#2) │ │ │ CrossJoin (location = Any) │ │ │ Scan (column_names = [n_nationkey, n_name, n_regionkey, n_comment], column_types │ │ │ = [Int32, Utf8, Int32, Utf8], function_name = read_parquet, location = ClientLocal, projection = [0, 1, │ │ │ 2, 3], table_ref = GlareDB/glaredb_next#3) │ │ │ Scan (column_names = [r_regionkey, r_name, r_comment], column_types = [Int32, │ │ │ Utf8, Utf8], function_name = read_parquet, location = ClientLocal, projection = [0, 1, 2], table_ref = │ │ │ GlareDB/glaredb_next#4) │ │ │ Project (location = Any, projections = [#11.0, GlareDB/glaredb_next#17.0], table_ref = GlareDB/glaredb_next#10) │ │ │ Aggregate (aggregates = [min(#6.3)], group_expressions = [#0.0], group_table_ref = GlareDB/glaredb_next#17, │ │ │ location = Any, table_ref = GlareDB/glaredb_next#11) │ │ │ Filter (location = Any, predicate = #0.0 = GlareDB/glaredb_next#6.0 AND GlareDB/glaredb_next#7.0 = GlareDB/glaredb_next#6.1 AND GlareDB/glaredb_next#7.3 = GlareDB/glaredb_next#8.0 AND │ │ │ GlareDB/glaredb_next#8.2 = GlareDB/glaredb_next#9.0 AND GlareDB/glaredb_next#9.1 = 'EUROPE') │ │ │ CrossJoin (location = Any) │ │ │ CrossJoin (location = Any) │ │ │ Scan (column_names = [ps_partkey, ps_suppkey, ps_availqty, ps_supplycost, │ │ │ ps_comment], column_types = [Int32, Int32, Int32, Decimal64(15,2), Utf8], function_name = read_parquet, │ │ │ location = ClientLocal, projection = [0, 1, 2, 3, 4], table_ref = GlareDB/glaredb_next#6) │ │ │ CrossJoin (location = Any) │ │ │ Scan (column_names = [s_suppkey, s_name, s_address, s_nationkey, s_phone, │ │ │ s_acctbal, s_comment], column_types = [Int32, Utf8, Utf8, Int32, Utf8, Decimal64(15,2), Utf8], │ │ │ function_name = read_parquet, location = ClientLocal, projection = [0, 1, 2, 3, 4, 5, 6], table_ref = │ │ │ GlareDB/glaredb_next#7) │ │ │ CrossJoin (location = Any) │ │ │ Scan (column_names = [n_nationkey, n_name, n_regionkey, n_comment], │ │ │ column_types = [Int32, Utf8, Int32, Utf8], function_name = read_parquet, location = ClientLocal, │ │ │ projection = [0, 1, 2, 3], table_ref = GlareDB/glaredb_next#8) │ │ │ Scan (column_names = [r_regionkey, r_name, r_comment], column_types = [Int32, │ │ │ Utf8, Utf8], function_name = read_parquet, location = ClientLocal, projection = [0, 1, 2], table_ref = │ │ │ GlareDB/glaredb_next#9) │ │ │ Distinct (location = Any, on = [#0.0]) │ │ │ MaterializationScan (location = Any, materialization_ref = MAT_0, table_refs = │ │ │ [#0, GlareDB/glaredb_next#1, GlareDB/glaredb_next#2, GlareDB/glaredb_next#3, GlareDB/glaredb_next#4]) │ │ │ CrossJoin (location = Any) │ │ │ Scan (column_names = [p_partkey, p_name, p_mfgr, p_brand, p_type, p_size, │ │ │ p_container, p_retailprice, p_comment], column_types = [Int32, Utf8, Utf8, Utf8, Utf8, Int32, Utf8, │ │ │ Decimal64(15,2), Utf8], function_name = read_parquet, location = ClientLocal, projection = [0, 1, 2, 3, │ │ │ 4, 5, 6, 7, 8], table_ref = #0) │ │ │ CrossJoin (location = Any) │ │ │ Scan (column_names = [s_suppkey, s_name, s_address, s_nationkey, s_phone, │ │ │ s_acctbal, s_comment], column_types = [Int32, Utf8, Utf8, Int32, Utf8, Decimal64(15,2), Utf8], │ │ │ function_name = read_parquet, location = ClientLocal, projection = [0, 1, 2, 3, 4, 5, 6], table_ref = │ │ │ GlareDB/glaredb_next#1) │ │ │ CrossJoin (location = Any) │ │ │ Scan (column_names = [ps_partkey, ps_suppkey, ps_availqty, ps_supplycost, │ │ │ ps_comment], column_types = [Int32, Int32, Int32, Decimal64(15,2), Utf8], function_name = read_parquet, │ │ │ location = ClientLocal, projection = [0, 1, 2, 3, 4], table_ref = GlareDB/glaredb_next#2) │ │ │ CrossJoin (location = Any) │ │ │ Scan (column_names = [n_nationkey, n_name, n_regionkey, n_comment], │ │ │ column_types = [Int32, Utf8, Int32, Utf8], function_name = read_parquet, location = ClientLocal, │ │ │ projection = [0, 1, 2, 3], table_ref = GlareDB/glaredb_next#3) │ │ │ Scan (column_names = [r_regionkey, r_name, r_comment], column_types = │ │ │ [Int32, Utf8, Utf8], function_name = read_parquet, location = ClientLocal, projection = [0, 1, 2], │ │ │ table_ref = GlareDB/glaredb_next#4) │ │ │ │ │ optimized │ Project (location = Any, projections = [#5.0, GlareDB/glaredb_next#5.1, GlareDB/glaredb_next#5.2, GlareDB/glaredb_next#5.3, GlareDB/glaredb_next#5.4, GlareDB/glaredb_next#5.5, GlareDB/glaredb_next#5.6, GlareDB/glaredb_next#5.7], table_ref = │ │ │ GlareDB/glaredb_next#14) │ │ │ Limit (limit = 100, location = Any) │ │ │ Order (expressions = [#5.8 desc nulls_first, GlareDB/glaredb_next#5.9 asc nulls_first, GlareDB/glaredb_next#5.10 asc nulls_first, GlareDB/glaredb_next#5.11 asc │ │ │ nulls_first], location = Any) │ │ │ Project (location = Any, projections = [#1.5, GlareDB/glaredb_next#1.1, GlareDB/glaredb_next#3.1, #0.0, #0.2, GlareDB/glaredb_next#1.2, GlareDB/glaredb_next#1.4, GlareDB/glaredb_next#1.6, GlareDB/glaredb_next#1.5, │ │ │ GlareDB/glaredb_next#3.1, GlareDB/glaredb_next#1.1, #0.0], table_ref = GlareDB/glaredb_next#5) │ │ │ Filter (location = Any, predicate = #0.0 = GlareDB/glaredb_next#2.0 AND GlareDB/glaredb_next#1.0 = GlareDB/glaredb_next#2.1 AND CAST(#0.5 TO Int64) = 15 │ │ │ AND ends_with(#0.4, '%BRASS') AND GlareDB/glaredb_next#1.3 = GlareDB/glaredb_next#3.0 AND GlareDB/glaredb_next#3.2 = GlareDB/glaredb_next#4.0 AND GlareDB/glaredb_next#4.1 = 'EUROPE' AND GlareDB/glaredb_next#2.3 = GlareDB/glaredb_next#10.0) │ │ │ ComparisonJoin (conditions = [#0.0 = GlareDB/glaredb_next#10.1], join_type = LEFT, location = Any) │ │ │ MaterializationScan (location = Any, materialization_ref = MAT_0, table_refs = [#0, GlareDB/glaredb_next#1, GlareDB/glaredb_next#2, │ │ │ GlareDB/glaredb_next#3, GlareDB/glaredb_next#4]) │ │ │ CrossJoin (location = Any) │ │ │ Scan (column_names = [p_partkey, p_name, p_mfgr, p_brand, p_type, p_size, p_container, │ │ │ p_retailprice, p_comment], column_types = [Int32, Utf8, Utf8, Utf8, Utf8, Int32, Utf8, Decimal64(15,2), │ │ │ Utf8], function_name = read_parquet, location = ClientLocal, projection = [0, 1, 2, 3, 4, 5, 6, 7, 8], │ │ │ table_ref = #0) │ │ │ CrossJoin (location = Any) │ │ │ Scan (column_names = [s_suppkey, s_name, s_address, s_nationkey, s_phone, s_acctbal, │ │ │ s_comment], column_types = [Int32, Utf8, Utf8, Int32, Utf8, Decimal64(15,2), Utf8], function_name = │ │ │ read_parquet, location = ClientLocal, projection = [0, 1, 2, 3, 4, 5, 6], table_ref = GlareDB/glaredb_next#1) │ │ │ CrossJoin (location = Any) │ │ │ Scan (column_names = [ps_partkey, ps_suppkey, ps_availqty, ps_supplycost, │ │ │ ps_comment], column_types = [Int32, Int32, Int32, Decimal64(15,2), Utf8], function_name = read_parquet, │ │ │ location = ClientLocal, projection = [0, 1, 2, 3, 4], table_ref = GlareDB/glaredb_next#2) │ │ │ CrossJoin (location = Any) │ │ │ Scan (column_names = [n_nationkey, n_name, n_regionkey, n_comment], column_types │ │ │ = [Int32, Utf8, Int32, Utf8], function_name = read_parquet, location = ClientLocal, projection = [0, 1, │ │ │ 2, 3], table_ref = GlareDB/glaredb_next#3) │ │ │ Scan (column_names = [r_regionkey, r_name, r_comment], column_types = [Int32, │ │ │ Utf8, Utf8], function_name = read_parquet, location = ClientLocal, projection = [0, 1, 2], table_ref = │ │ │ GlareDB/glaredb_next#4) │ │ │ Project (location = Any, projections = [#11.0, GlareDB/glaredb_next#17.0], table_ref = GlareDB/glaredb_next#10) │ │ │ Aggregate (aggregates = [min(#6.3)], group_expressions = [#0.0], group_table_ref = GlareDB/glaredb_next#17, │ │ │ location = Any, table_ref = GlareDB/glaredb_next#11) │ │ │ ComparisonJoin (conditions = [#6.0 = #0.0], join_type = INNER, location = Any) │ │ │ ComparisonJoin (conditions = [#6.1 = GlareDB/glaredb_next#7.0], join_type = INNER, location = Any) │ │ │ Scan (column_names = [ps_partkey, ps_suppkey, ps_availqty, ps_supplycost, │ │ │ ps_comment], column_types = [Int32, Int32, Int32, Decimal64(15,2), Utf8], function_name = read_parquet, │ │ │ location = ClientLocal, projection = [0, 1, 2, 3, 4], table_ref = GlareDB/glaredb_next#6) │ │ │ ComparisonJoin (conditions = [#7.3 = GlareDB/glaredb_next#8.0], join_type = INNER, location = Any) │ │ │ Scan (column_names = [s_suppkey, s_name, s_address, s_nationkey, s_phone, │ │ │ s_acctbal, s_comment], column_types = [Int32, Utf8, Utf8, Int32, Utf8, Decimal64(15,2), Utf8], │ │ │ function_name = read_parquet, location = ClientLocal, projection = [0, 1, 2, 3, 4, 5, 6], table_ref = │ │ │ GlareDB/glaredb_next#7) │ │ │ ComparisonJoin (conditions = [#8.2 = GlareDB/glaredb_next#9.0], join_type = INNER, location = Any) │ │ │ Scan (column_names = [n_nationkey, n_name, n_regionkey, n_comment], │ │ │ column_types = [Int32, Utf8, Int32, Utf8], function_name = read_parquet, location = ClientLocal, │ │ │ projection = [0, 1, 2, 3], table_ref = GlareDB/glaredb_next#8) │ │ │ Filter (location = Any, predicate = GlareDB/glaredb_next#9.1 = 'EUROPE') │ │ │ Scan (column_names = [r_regionkey, r_name, r_comment], column_types = [Int32, │ │ │ Utf8, Utf8], function_name = read_parquet, location = ClientLocal, projection = [0, 1, 2], table_ref = │ │ │ GlareDB/glaredb_next#9) │ │ │ Distinct (location = Any, on = [#0.0]) │ │ │ MaterializationScan (location = Any, materialization_ref = MAT_0, table_refs = [#0, │ │ │ GlareDB/glaredb_next#1, GlareDB/glaredb_next#2, GlareDB/glaredb_next#3, GlareDB/glaredb_next#4]) │ │ │ CrossJoin (location = Any) │ │ │ Scan (column_names = [p_partkey, p_name, p_mfgr, p_brand, p_type, p_size, │ │ │ p_container, p_retailprice, p_comment], column_types = [Int32, Utf8, Utf8, Utf8, Utf8, Int32, Utf8, │ │ │ Decimal64(15,2), Utf8], function_name = read_parquet, location = ClientLocal, projection = [0, 1, 2, 3, │ │ │ 4, 5, 6, 7, 8], table_ref = #0) │ │ │ CrossJoin (location = Any) │ │ │ Scan (column_names = [s_suppkey, s_name, s_address, s_nationkey, s_phone, │ │ │ s_acctbal, s_comment], column_types = [Int32, Utf8, Utf8, Int32, Utf8, Decimal64(15,2), Utf8], │ │ │ function_name = read_parquet, location = ClientLocal, projection = [0, 1, 2, 3, 4, 5, 6], table_ref = │ │ │ GlareDB/glaredb_next#1) │ │ │ CrossJoin (location = Any) │ │ │ Scan (column_names = [ps_partkey, ps_suppkey, ps_availqty, ps_supplycost, │ │ │ ps_comment], column_types = [Int32, Int32, Int32, Decimal64(15,2), Utf8], function_name = read_parquet, │ │ │ location = ClientLocal, projection = [0, 1, 2, 3, 4], table_ref = GlareDB/glaredb_next#2) │ │ │ CrossJoin (location = Any) │ │ │ Scan (column_names = [n_nationkey, n_name, n_regionkey, n_comment], │ │ │ column_types = [Int32, Utf8, Int32, Utf8], function_name = read_parquet, location = ClientLocal, │ │ │ projection = [0, 1, 2, 3], table_ref = GlareDB/glaredb_next#3) │ │ │ Scan (column_names = [r_regionkey, r_name, r_comment], column_types = │ │ │ [Int32, Utf8, Utf8], function_name = read_parquet, location = ClientLocal, projection = [0, 1, 2], │ │ │ table_ref = GlareDB/glaredb_next#4) │ │ │ │ │ physical │ IntermediatePipelineGroups │ │ │ IntermediatePipelineGroup local │ │ │ IntermediatePipeline 9 (Sink = InGroup {pipeline_id: 6, operator_idx: 4, input_idx: 0}, Source = │ │ │ InPipeline) │ │ │ TableFunction (partitioning_requirement = None) │ │ │ IntermediatePipeline 6 (Sink = InGroup {pipeline_id: 5, operator_idx: 0, input_idx: 0}, Source = │ │ │ InPipeline) │ │ │ TableFunction (partitioning_requirement = None) │ │ │ Filter (partitioning_requirement = None, predicate = =(@1, EUROPE)) │ │ │ HashJoin (conditions = [(LEFT @2) = (RIGHT @0)], equality = (LEFT @2) = (RIGHT @0), join_type = │ │ │ INNER, partitioning_requirement = None) │ │ │ HashJoin (conditions = [(LEFT @3) = (RIGHT @0)], equality = (LEFT @3) = (RIGHT @0), join_type = │ │ │ INNER, partitioning_requirement = None) │ │ │ HashJoin (conditions = [(LEFT @1) = (RIGHT @0)], equality = (LEFT @1) = (RIGHT @0), join_type = │ │ │ INNER, partitioning_requirement = None) │ │ │ IntermediatePipeline 7 (Sink = InGroup {pipeline_id: 6, operator_idx: 2, input_idx: 0}, Source = │ │ │ InPipeline) │ │ │ TableFunction (partitioning_requirement = None) │ │ │ IntermediatePipeline 5 (Sink = InPipeline, Source = Materialization {materialization_ref: MAT_0}) │ │ │ HashJoin (conditions = [(LEFT @0) = (RIGHT @0)], equality = (LEFT @0) = (RIGHT @0), join_type = │ │ │ INNER, partitioning_requirement = None) │ │ │ Project (partitioning_requirement = None, projections = [@3, @19]) │ │ │ HashAggregate (aggregate_columns = [0], partitioning_requirement = None) │ │ │ Project (partitioning_requirement = None, projections = [@0, @1]) │ │ │ HashJoin (conditions = [(LEFT @0) = (RIGHT @1)], equality = (LEFT @0) = (RIGHT @1), join_type = │ │ │ LEFT, partitioning_requirement = None) │ │ │ Filter (partitioning_requirement = None, predicate = and(and(and(and(and(and(and(=(@0, @16), │ │ │ =(@9, @17)), =(CAST(@5 TO Int64), 15)), ends_with(@4, %BRASS)), =(@12, @21)), =(@23, @25)), =(@26, │ │ │ EUROPE)), =(@19, @28))) │ │ │ Project (partitioning_requirement = None, projections = [@14, @10, @22, @0, @2, @11, @13, @15, │ │ │ @14, @22, @10, @0]) │ │ │ LocalSort (partitioning_requirement = None) │ │ │ MergeSorted (partitioning_requirement = None) │ │ │ IntermediatePipeline 8 (Sink = InGroup {pipeline_id: 6, operator_idx: 3, input_idx: 0}, Source = │ │ │ InPipeline) │ │ │ TableFunction (partitioning_requirement = None) │ │ │ IntermediatePipeline 10 (Sink = InGroup {pipeline_id: 5, operator_idx: 4, input_idx: 0}, Source = │ │ │ Materialization {materialization_ref: MAT_0}) │ │ │ IntermediatePipeline 11 (Sink = QueryOutput, Source = OtherPipeline {pipeline_id: 5}) │ │ │ Limit (limit = 100, partitioning_requirement = Some(1)) │ │ │ Project (partitioning_requirement = None, projections = [@0, @1, @2, @3, @4, @5, @6, @7]) │ │ │ IntermediatePipelineGroup remote │ │ │ │ └───────────┴─────────────────────────────────────────────────────────────────────────────────────────────────────────┘
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Currently just including the local/remote groups which reference materializations, but materializations aren't displayed:
The text was updated successfully, but these errors were encountered: