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reimplement push_down_projection and prune_column. #4465

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Feb 28, 2023
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reimplement push_down_projection and prune_column. #4465

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c3319da
reimplement push_down_projection and prune_column
jackwener Feb 25, 2023
636e5fe
fix COUNT(UInt8(1))
jackwener Feb 26, 2023
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23 changes: 14 additions & 9 deletions benchmarks/expected-plans/q10.txt
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Original file line number Diff line number Diff line change
@@ -1,12 +1,17 @@
Sort: revenue DESC NULLS FIRST
Projection: customer.c_custkey, customer.c_name, SUM(lineitem.l_extendedprice * Int64(1) - lineitem.l_discount) AS revenue, customer.c_acctbal, nation.n_name, customer.c_address, customer.c_phone, customer.c_comment
Aggregate: groupBy=[[customer.c_custkey, customer.c_name, customer.c_acctbal, customer.c_phone, nation.n_name, customer.c_address, customer.c_comment]], aggr=[[SUM(CAST(lineitem.l_extendedprice AS Decimal128(38, 4)) * CAST(Decimal128(Some(100),23,2) - CAST(lineitem.l_discount AS Decimal128(23, 2)) AS Decimal128(38, 4))) AS SUM(lineitem.l_extendedprice * Int64(1) - lineitem.l_discount)]]
Inner Join: customer.c_nationkey = nation.n_nationkey
Inner Join: orders.o_orderkey = lineitem.l_orderkey
Inner Join: customer.c_custkey = orders.o_custkey
TableScan: customer projection=[c_custkey, c_name, c_address, c_nationkey, c_phone, c_acctbal, c_comment]
Filter: orders.o_orderdate >= Date32("8674") AND orders.o_orderdate < Date32("8766")
TableScan: orders projection=[o_orderkey, o_custkey, o_orderdate]
Filter: lineitem.l_returnflag = Utf8("R")
TableScan: lineitem projection=[l_orderkey, l_extendedprice, l_discount, l_returnflag]
TableScan: nation projection=[n_nationkey, n_name]
Projection: customer.c_custkey, customer.c_name, customer.c_address, customer.c_phone, customer.c_acctbal, customer.c_comment, lineitem.l_extendedprice, lineitem.l_discount, nation.n_name
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@jackwener jackwener Dec 9, 2022 •
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We can find some new projection happen above join. because I prune column for Join

For example:

table a [id] b [id] c [id]
select c.id from (select * from a join b on a.id = b.id) join c on a.id = c.id.

we need add projection above inside join (a b), because b.id is just used for condition.
We need projection prune `b.id`.

original:
       project c.id
         Join
    Join    c(id)
a(id)  b(id)

->
        project c.id
            Join
project(a.id)  c(id)
    Join
a(id)  b(id)

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@alamb alamb Feb 17, 2023

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So the idea is that the Projection nodes above the join are added to make it clear what columns that come out of the join are actually needed above it?

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@jackwener jackwener Feb 19, 2023

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Yes, the Projection nodes above the join is used to just get columns that we need to use.

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@ygf11 ygf11 Feb 19, 2023 •
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Maybe it is relative to build_join_schema. Some optimizer rules call this function.
I think it is ok for calling it before pushdown projection, but I guess it is not correct after push down projection.

For the query:

select a.id from a join b on a.id = b.id

we call it after pushdown projection:

  1. schema(a): a.id
  2. schema(b): b.id

build_join_schema will merge left and right, the result is a.id + b.id, but the expected result should be only a.id.

Maybe we can fix it first, and then we will not need the projection any more.

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@jackwener jackwener Feb 19, 2023 •
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I'm sorry for this comment is easily misunderstood. I have corrected it.

Inner Join: customer.c_nationkey = nation.n_nationkey
Projection: customer.c_custkey, customer.c_name, customer.c_address, customer.c_nationkey, customer.c_phone, customer.c_acctbal, customer.c_comment, lineitem.l_extendedprice, lineitem.l_discount
Inner Join: orders.o_orderkey = lineitem.l_orderkey
Projection: customer.c_custkey, customer.c_name, customer.c_address, customer.c_nationkey, customer.c_phone, customer.c_acctbal, customer.c_comment, orders.o_orderkey
Inner Join: customer.c_custkey = orders.o_custkey
TableScan: customer projection=[c_custkey, c_name, c_address, c_nationkey, c_phone, c_acctbal, c_comment]
Projection: orders.o_orderkey, orders.o_custkey
Filter: orders.o_orderdate >= Date32("8674") AND orders.o_orderdate < Date32("8766")
TableScan: orders projection=[o_orderkey, o_custkey, o_orderdate]
Projection: lineitem.l_orderkey, lineitem.l_extendedprice, lineitem.l_discount
Filter: lineitem.l_returnflag = Utf8("R")
TableScan: lineitem projection=[l_orderkey, l_extendedprice, l_discount, l_returnflag]
TableScan: nation projection=[n_nationkey, n_name]
30 changes: 18 additions & 12 deletions benchmarks/expected-plans/q11.txt
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Expand Up @@ -3,18 +3,24 @@ Sort: value DESC NULLS FIRST
Filter: CAST(SUM(partsupp.ps_supplycost * partsupp.ps_availqty) AS Decimal128(38, 15)) > CAST(__scalar_sq_1.__value AS Decimal128(38, 15))
CrossJoin:
Aggregate: groupBy=[[partsupp.ps_partkey]], aggr=[[SUM(CAST(partsupp.ps_supplycost AS Decimal128(26, 2)) * CAST(partsupp.ps_availqty AS Decimal128(26, 2)))]]
Inner Join: supplier.s_nationkey = nation.n_nationkey
Inner Join: partsupp.ps_suppkey = supplier.s_suppkey
TableScan: partsupp projection=[ps_partkey, ps_suppkey, ps_availqty, ps_supplycost]
TableScan: supplier projection=[s_suppkey, s_nationkey]
Filter: nation.n_name = Utf8("GERMANY")
TableScan: nation projection=[n_nationkey, n_name]
SubqueryAlias: __scalar_sq_1
Projection: CAST(SUM(partsupp.ps_supplycost * partsupp.ps_availqty) AS Float64) * Float64(0.0001) AS __value
Aggregate: groupBy=[[]], aggr=[[SUM(CAST(partsupp.ps_supplycost AS Decimal128(26, 2)) * CAST(partsupp.ps_availqty AS Decimal128(26, 2)))]]
Inner Join: supplier.s_nationkey = nation.n_nationkey
Projection: partsupp.ps_partkey, partsupp.ps_availqty, partsupp.ps_supplycost
Inner Join: supplier.s_nationkey = nation.n_nationkey
Projection: partsupp.ps_partkey, partsupp.ps_availqty, partsupp.ps_supplycost, supplier.s_nationkey
Inner Join: partsupp.ps_suppkey = supplier.s_suppkey
TableScan: partsupp projection=[ps_suppkey, ps_availqty, ps_supplycost]
TableScan: partsupp projection=[ps_partkey, ps_suppkey, ps_availqty, ps_supplycost]
TableScan: supplier projection=[s_suppkey, s_nationkey]
Projection: nation.n_nationkey
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@jackwener jackwener Feb 26, 2023

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Here Filter will output two columns, but we just need one column nation.n_nationkey, so add projection to prune column

Filter: nation.n_name = Utf8("GERMANY")
TableScan: nation projection=[n_nationkey, n_name]
TableScan: nation projection=[n_nationkey, n_name]
SubqueryAlias: __scalar_sq_1
Projection: CAST(SUM(partsupp.ps_supplycost * partsupp.ps_availqty) AS Float64) * Float64(0.0001) AS __value
Aggregate: groupBy=[[]], aggr=[[SUM(CAST(partsupp.ps_supplycost AS Decimal128(26, 2)) * CAST(partsupp.ps_availqty AS Decimal128(26, 2)))]]
Projection: partsupp.ps_availqty, partsupp.ps_supplycost
Inner Join: supplier.s_nationkey = nation.n_nationkey
Projection: partsupp.ps_availqty, partsupp.ps_supplycost, supplier.s_nationkey
Inner Join: partsupp.ps_suppkey = supplier.s_suppkey
TableScan: partsupp projection=[ps_suppkey, ps_availqty, ps_supplycost]
TableScan: supplier projection=[s_suppkey, s_nationkey]
Projection: nation.n_nationkey
Filter: nation.n_name = Utf8("GERMANY")
TableScan: nation projection=[n_nationkey, n_name]
10 changes: 6 additions & 4 deletions benchmarks/expected-plans/q12.txt
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Sort: lineitem.l_shipmode ASC NULLS LAST
Projection: lineitem.l_shipmode, SUM(CASE WHEN orders.o_orderpriority = Utf8("1-URGENT") OR orders.o_orderpriority = Utf8("2-HIGH") THEN Int64(1) ELSE Int64(0) END) AS high_line_count, SUM(CASE WHEN orders.o_orderpriority != Utf8("1-URGENT") AND orders.o_orderpriority != Utf8("2-HIGH") THEN Int64(1) ELSE Int64(0) END) AS low_line_count
Aggregate: groupBy=[[lineitem.l_shipmode]], aggr=[[SUM(CASE WHEN orders.o_orderpriority = Utf8("1-URGENT") OR orders.o_orderpriority = Utf8("2-HIGH") THEN Int64(1) ELSE Int64(0) END), SUM(CASE WHEN orders.o_orderpriority != Utf8("1-URGENT") AND orders.o_orderpriority != Utf8("2-HIGH") THEN Int64(1) ELSE Int64(0) END)]]
Inner Join: lineitem.l_orderkey = orders.o_orderkey
Filter: (lineitem.l_shipmode = Utf8("SHIP") OR lineitem.l_shipmode = Utf8("MAIL")) AND lineitem.l_commitdate < lineitem.l_receiptdate AND lineitem.l_shipdate < lineitem.l_commitdate AND lineitem.l_receiptdate >= Date32("8766") AND lineitem.l_receiptdate < Date32("9131")
TableScan: lineitem projection=[l_orderkey, l_shipdate, l_commitdate, l_receiptdate, l_shipmode]
TableScan: orders projection=[o_orderkey, o_orderpriority]
Projection: lineitem.l_shipmode, orders.o_orderpriority
Inner Join: lineitem.l_orderkey = orders.o_orderkey
Projection: lineitem.l_orderkey, lineitem.l_shipmode
Filter: (lineitem.l_shipmode = Utf8("SHIP") OR lineitem.l_shipmode = Utf8("MAIL")) AND lineitem.l_commitdate < lineitem.l_receiptdate AND lineitem.l_shipdate < lineitem.l_commitdate AND lineitem.l_receiptdate >= Date32("8766") AND lineitem.l_receiptdate < Date32("9131")
TableScan: lineitem projection=[l_orderkey, l_shipdate, l_commitdate, l_receiptdate, l_shipmode]
TableScan: orders projection=[o_orderkey, o_orderpriority]
10 changes: 6 additions & 4 deletions benchmarks/expected-plans/q13.txt
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Expand Up @@ -5,7 +5,9 @@ Sort: custdist DESC NULLS FIRST, c_count DESC NULLS FIRST
SubqueryAlias: c_orders
Projection: COUNT(orders.o_orderkey)
Aggregate: groupBy=[[customer.c_custkey]], aggr=[[COUNT(orders.o_orderkey)]]
Left Join: customer.c_custkey = orders.o_custkey
TableScan: customer projection=[c_custkey]
Filter: orders.o_comment NOT LIKE Utf8("%special%requests%")
TableScan: orders projection=[o_orderkey, o_custkey, o_comment]
Projection: customer.c_custkey, orders.o_orderkey
Left Join: customer.c_custkey = orders.o_custkey
TableScan: customer projection=[c_custkey]
Projection: orders.o_orderkey, orders.o_custkey
Filter: orders.o_comment NOT LIKE Utf8("%special%requests%")
TableScan: orders projection=[o_orderkey, o_custkey, o_comment]
5 changes: 3 additions & 2 deletions benchmarks/expected-plans/q14.txt
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Expand Up @@ -2,6 +2,7 @@ Projection: Float64(100) * CAST(SUM(CASE WHEN part.p_type LIKE Utf8("PROMO%") T
Aggregate: groupBy=[[]], aggr=[[SUM(CASE WHEN part.p_type LIKE Utf8("PROMO%") THEN CAST(lineitem.l_extendedprice AS Decimal128(38, 4)) * CAST(Decimal128(Some(100),23,2) - CAST(lineitem.l_discount AS Decimal128(23, 2)) AS Decimal128(38, 4))CAST(Decimal128(Some(100),23,2) - CAST(lineitem.l_discount AS Decimal128(23, 2)) AS Decimal128(38, 4))Decimal128(Some(100),23,2) - CAST(lineitem.l_discount AS Decimal128(23, 2))CAST(lineitem.l_discount AS Decimal128(23, 2))lineitem.l_discountDecimal128(Some(100),23,2)CAST(lineitem.l_extendedprice AS Decimal128(38, 4))lineitem.l_extendedprice AS lineitem.l_extendedprice * Decimal128(Some(100),23,2) - lineitem.l_discount ELSE Decimal128(Some(0),38,4) END) AS SUM(CASE WHEN part.p_type LIKE Utf8("PROMO%") THEN lineitem.l_extendedprice * Int64(1) - lineitem.l_discount ELSE Int64(0) END), SUM(CAST(lineitem.l_extendedprice AS Decimal128(38, 4)) * CAST(Decimal128(Some(100),23,2) - CAST(lineitem.l_discount AS Decimal128(23, 2)) AS Decimal128(38, 4))CAST(Decimal128(Some(100),23,2) - CAST(lineitem.l_discount AS Decimal128(23, 2)) AS Decimal128(38, 4))Decimal128(Some(100),23,2) - CAST(lineitem.l_discount AS Decimal128(23, 2))CAST(lineitem.l_discount AS Decimal128(23, 2))lineitem.l_discountDecimal128(Some(100),23,2)CAST(lineitem.l_extendedprice AS Decimal128(38, 4))lineitem.l_extendedprice AS lineitem.l_extendedprice * Decimal128(Some(100),23,2) - lineitem.l_discount) AS SUM(lineitem.l_extendedprice * Int64(1) - lineitem.l_discount)]]
Projection: CAST(lineitem.l_extendedprice AS Decimal128(38, 4)) * CAST(Decimal128(Some(100),23,2) - CAST(lineitem.l_discount AS Decimal128(23, 2)) AS Decimal128(38, 4)) AS CAST(lineitem.l_extendedprice AS Decimal128(38, 4)) * CAST(Decimal128(Some(100),23,2) - CAST(lineitem.l_discount AS Decimal128(23, 2)) AS Decimal128(38, 4))CAST(Decimal128(Some(100),23,2) - CAST(lineitem.l_discount AS Decimal128(23, 2)) AS Decimal128(38, 4))Decimal128(Some(100),23,2) - CAST(lineitem.l_discount AS Decimal128(23, 2))CAST(lineitem.l_discount AS Decimal128(23, 2))lineitem.l_discountDecimal128(Some(100),23,2)CAST(lineitem.l_extendedprice AS Decimal128(38, 4))lineitem.l_extendedprice, part.p_type
Inner Join: lineitem.l_partkey = part.p_partkey
Filter: lineitem.l_shipdate >= Date32("9374") AND lineitem.l_shipdate < Date32("9404")
TableScan: lineitem projection=[l_partkey, l_extendedprice, l_discount, l_shipdate]
Projection: lineitem.l_partkey, lineitem.l_extendedprice, lineitem.l_discount
Filter: lineitem.l_shipdate >= Date32("9374") AND lineitem.l_shipdate < Date32("9404")
TableScan: lineitem projection=[l_partkey, l_extendedprice, l_discount, l_shipdate]
TableScan: part projection=[p_partkey, p_type]
21 changes: 12 additions & 9 deletions benchmarks/expected-plans/q15.txt
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Expand Up @@ -2,19 +2,22 @@ EmptyRelation
Sort: supplier.s_suppkey ASC NULLS LAST
Projection: supplier.s_suppkey, supplier.s_name, supplier.s_address, supplier.s_phone, revenue0.total_revenue
Inner Join: revenue0.total_revenue = __scalar_sq_1.__value
Inner Join: supplier.s_suppkey = revenue0.supplier_no
TableScan: supplier projection=[s_suppkey, s_name, s_address, s_phone]
SubqueryAlias: revenue0
Projection: lineitem.l_suppkey AS supplier_no, SUM(lineitem.l_extendedprice * Int64(1) - lineitem.l_discount) AS total_revenue
Aggregate: groupBy=[[lineitem.l_suppkey]], aggr=[[SUM(CAST(lineitem.l_extendedprice AS Decimal128(38, 4)) * CAST(Decimal128(Some(100),23,2) - CAST(lineitem.l_discount AS Decimal128(23, 2)) AS Decimal128(38, 4))) AS SUM(lineitem.l_extendedprice * Int64(1) - lineitem.l_discount)]]
Filter: lineitem.l_shipdate >= Date32("9496") AND lineitem.l_shipdate < Date32("9587")
TableScan: lineitem projection=[l_suppkey, l_extendedprice, l_discount, l_shipdate]
Projection: supplier.s_suppkey, supplier.s_name, supplier.s_address, supplier.s_phone, revenue0.total_revenue
Inner Join: supplier.s_suppkey = revenue0.supplier_no
TableScan: supplier projection=[s_suppkey, s_name, s_address, s_phone]
SubqueryAlias: revenue0
Projection: lineitem.l_suppkey AS supplier_no, SUM(lineitem.l_extendedprice * Int64(1) - lineitem.l_discount) AS total_revenue
Aggregate: groupBy=[[lineitem.l_suppkey]], aggr=[[SUM(CAST(lineitem.l_extendedprice AS Decimal128(38, 4)) * CAST(Decimal128(Some(100),23,2) - CAST(lineitem.l_discount AS Decimal128(23, 2)) AS Decimal128(38, 4))) AS SUM(lineitem.l_extendedprice * Int64(1) - lineitem.l_discount)]]
Projection: lineitem.l_suppkey, lineitem.l_extendedprice, lineitem.l_discount
Filter: lineitem.l_shipdate >= Date32("9496") AND lineitem.l_shipdate < Date32("9587")
TableScan: lineitem projection=[l_suppkey, l_extendedprice, l_discount, l_shipdate]
SubqueryAlias: __scalar_sq_1
Projection: MAX(revenue0.total_revenue) AS __value
Aggregate: groupBy=[[]], aggr=[[MAX(revenue0.total_revenue)]]
SubqueryAlias: revenue0
Projection: SUM(lineitem.l_extendedprice * Int64(1) - lineitem.l_discount) AS total_revenue
Aggregate: groupBy=[[lineitem.l_suppkey]], aggr=[[SUM(CAST(lineitem.l_extendedprice AS Decimal128(38, 4)) * CAST(Decimal128(Some(100),23,2) - CAST(lineitem.l_discount AS Decimal128(23, 2)) AS Decimal128(38, 4))) AS SUM(lineitem.l_extendedprice * Int64(1) - lineitem.l_discount)]]
Filter: lineitem.l_shipdate >= Date32("9496") AND lineitem.l_shipdate < Date32("9587")
TableScan: lineitem projection=[l_suppkey, l_extendedprice, l_discount, l_shipdate]
Projection: lineitem.l_suppkey, lineitem.l_extendedprice, lineitem.l_discount
Filter: lineitem.l_shipdate >= Date32("9496") AND lineitem.l_shipdate < Date32("9587")
TableScan: lineitem projection=[l_suppkey, l_extendedprice, l_discount, l_shipdate]
EmptyRelation
9 changes: 5 additions & 4 deletions benchmarks/expected-plans/q16.txt
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Expand Up @@ -3,10 +3,11 @@ Sort: supplier_cnt DESC NULLS FIRST, part.p_brand ASC NULLS LAST, part.p_type AS
Aggregate: groupBy=[[group_alias_0, group_alias_1, group_alias_2]], aggr=[[COUNT(alias1)]]
Aggregate: groupBy=[[part.p_brand AS group_alias_0, part.p_type AS group_alias_1, part.p_size AS group_alias_2, partsupp.ps_suppkey AS alias1]], aggr=[[]]
LeftAnti Join: partsupp.ps_suppkey = __correlated_sq_1.s_suppkey
Inner Join: partsupp.ps_partkey = part.p_partkey
TableScan: partsupp projection=[ps_partkey, ps_suppkey]
Filter: part.p_brand != Utf8("Brand#45") AND part.p_type NOT LIKE Utf8("MEDIUM POLISHED%") AND part.p_size IN ([Int32(49), Int32(14), Int32(23), Int32(45), Int32(19), Int32(3), Int32(36), Int32(9)])
TableScan: part projection=[p_partkey, p_brand, p_type, p_size]
Projection: partsupp.ps_suppkey, part.p_brand, part.p_type, part.p_size
Inner Join: partsupp.ps_partkey = part.p_partkey
TableScan: partsupp projection=[ps_partkey, ps_suppkey]
Filter: part.p_brand != Utf8("Brand#45") AND part.p_type NOT LIKE Utf8("MEDIUM POLISHED%") AND part.p_size IN ([Int32(49), Int32(14), Int32(23), Int32(45), Int32(19), Int32(3), Int32(36), Int32(9)])
TableScan: part projection=[p_partkey, p_brand, p_type, p_size]
SubqueryAlias: __correlated_sq_1
Projection: supplier.s_suppkey AS s_suppkey
Filter: supplier.s_comment LIKE Utf8("%Customer%Complaints%")
Expand Down
24 changes: 14 additions & 10 deletions benchmarks/expected-plans/q17.txt
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Projection: CAST(SUM(lineitem.l_extendedprice) AS Float64) / Float64(7) AS avg_yearly
Aggregate: groupBy=[[]], aggr=[[SUM(lineitem.l_extendedprice)]]
Filter: CAST(lineitem.l_quantity AS Decimal128(30, 15)) < CAST(__scalar_sq_1.__value AS Decimal128(30, 15))
Inner Join: part.p_partkey = __scalar_sq_1.l_partkey, lineitem.l_partkey = __scalar_sq_1.l_partkey
Inner Join: lineitem.l_partkey = part.p_partkey
TableScan: lineitem projection=[l_partkey, l_quantity, l_extendedprice]
Filter: part.p_brand = Utf8("Brand#23") AND part.p_container = Utf8("MED BOX")
TableScan: part projection=[p_partkey, p_brand, p_container]
SubqueryAlias: __scalar_sq_1
Projection: lineitem.l_partkey, Float64(0.2) * CAST(AVG(lineitem.l_quantity) AS Float64) AS __value
Aggregate: groupBy=[[lineitem.l_partkey]], aggr=[[AVG(lineitem.l_quantity)]]
TableScan: lineitem projection=[l_partkey, l_quantity]
Projection: lineitem.l_extendedprice
Filter: CAST(lineitem.l_quantity AS Decimal128(30, 15)) < CAST(__scalar_sq_1.__value AS Decimal128(30, 15)) AND __scalar_sq_1.l_partkey = lineitem.l_partkey
Projection: lineitem.l_partkey, lineitem.l_quantity, lineitem.l_extendedprice, __scalar_sq_1.l_partkey, __scalar_sq_1.__value
Inner Join: part.p_partkey = __scalar_sq_1.l_partkey
Filter: part.p_partkey = lineitem.l_partkey AND lineitem.l_partkey = part.p_partkey
Inner Join: lineitem.l_partkey = part.p_partkey
TableScan: lineitem projection=[l_partkey, l_quantity, l_extendedprice]
Projection: part.p_partkey
Filter: part.p_brand = Utf8("Brand#23") AND part.p_container = Utf8("MED BOX")
TableScan: part projection=[p_partkey, p_brand, p_container]
SubqueryAlias: __scalar_sq_1
Projection: lineitem.l_partkey, Float64(0.2) * CAST(AVG(lineitem.l_quantity) AS Float64) AS __value
Aggregate: groupBy=[[lineitem.l_partkey]], aggr=[[AVG(lineitem.l_quantity)]]
TableScan: lineitem projection=[l_partkey, l_quantity]
12 changes: 7 additions & 5 deletions benchmarks/expected-plans/q18.txt
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Sort: orders.o_totalprice DESC NULLS FIRST, orders.o_orderdate ASC NULLS LAST
Aggregate: groupBy=[[customer.c_name, customer.c_custkey, orders.o_orderkey, orders.o_orderdate, orders.o_totalprice]], aggr=[[SUM(lineitem.l_quantity)]]
LeftSemi Join: orders.o_orderkey = __correlated_sq_1.l_orderkey
Inner Join: orders.o_orderkey = lineitem.l_orderkey
Inner Join: customer.c_custkey = orders.o_custkey
TableScan: customer projection=[c_custkey, c_name]
TableScan: orders projection=[o_orderkey, o_custkey, o_totalprice, o_orderdate]
TableScan: lineitem projection=[l_orderkey, l_quantity]
Projection: customer.c_custkey, customer.c_name, orders.o_orderkey, orders.o_totalprice, orders.o_orderdate, lineitem.l_quantity
Inner Join: orders.o_orderkey = lineitem.l_orderkey
Projection: customer.c_custkey, customer.c_name, orders.o_orderkey, orders.o_totalprice, orders.o_orderdate
Inner Join: customer.c_custkey = orders.o_custkey
TableScan: customer projection=[c_custkey, c_name]
TableScan: orders projection=[o_orderkey, o_custkey, o_totalprice, o_orderdate]
TableScan: lineitem projection=[l_orderkey, l_quantity]
SubqueryAlias: __correlated_sq_1
Projection: lineitem.l_orderkey AS l_orderkey
Filter: SUM(lineitem.l_quantity) > Decimal128(Some(30000),25,2)
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