milenkovicm commented on issue #1296:
URL:
https://github.com/apache/datafusion-ballista/issues/1296#issuecomment-3223060640
```text
ShuffleWriterExec: partitions:Some(Hash([Column { name: "i_category", index:
0 }, Column { name: "i_brand", index: 1 }, Column { name: "s_store_name",
index: 2 }, Column { name: "s_company_name", index: 3 }, Column { name:
"CAST(v1.rn AS Decimal128(21, 0))", index: 9 }], 16))
ProjectionExec: expr=[i_category@0 as i_category, i_brand@1 as i_brand,
s_store_name@2 as s_store_name, s_company_name@3 as s_company_name, d_year@4 as
d_year, d_moy@5 as d_moy, sum(store_sales.ss_sales_price)@6 as sum_sales,
avg(sum(store_sales.ss_sales_price)) PARTITION BY [item.i_category,
item.i_brand, store.s_store_name, store.s_company_name, date_dim.d_year] ROWS
BETWEEN UNBOUNDED PRECEDING AND UNBOUNDED FOLLOWING@8 as avg_monthly_sales,
rank() PARTITION BY [item.i_category, item.i_brand, store.s_store_name,
store.s_company_name] ORDER BY [date_dim.d_year ASC NULLS LAST, date_dim.d_moy
ASC NULLS LAST] RANGE BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW@7 as rn,
CAST(rank() PARTITION BY [item.i_category, item.i_brand, store.s_store_name,
store.s_company_name] ORDER BY [date_dim.d_year ASC NULLS LAST, date_dim.d_moy
ASC NULLS LAST] RANGE BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW@7 AS
Decimal128(21, 0)) as CAST(v1.rn AS Decimal128(21, 0))]
CoalesceBatchesExec: target_batch_size=8192
FilterExec: __common_expr_3@0 AND CASE WHEN __common_expr_3@0 THEN
abs(sum(store_sales.ss_sales_price)@7 - avg(sum(store_sales.ss_sales_price))
PARTITION BY [item.i_category, item.i_brand, store.s_store_name,
store.s_company_name, date_dim.d_year] ROWS BETWEEN UNBOUNDED PRECEDING AND
UNBOUNDED FOLLOWING@9) / avg(sum(store_sales.ss_sales_price)) PARTITION BY
[item.i_category, item.i_brand, store.s_store_name, store.s_company_name,
date_dim.d_year] ROWS BETWEEN UNBOUNDED PRECEDING AND UNBOUNDED FOLLOWING@9 END
> 0.1, projection=[i_category@1, i_brand@2, s_store_name@3, s_company_name@4,
d_year@5, d_moy@6, sum(store_sales.ss_sales_price)@7, rank() PARTITION BY
[item.i_category, item.i_brand, store.s_store_name, store.s_company_name] ORDER
BY [date_dim.d_year ASC NULLS LAST, date_dim.d_moy ASC NULLS LAST] RANGE
BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW@8,
avg(sum(store_sales.ss_sales_price)) PARTITION BY [item.i_category,
item.i_brand, store.s_store_name, store.s_company_name,
date_dim.d_year] ROWS BETWEEN UNBOUNDED PRECEDING AND UNBOUNDED FOLLOWING@9]
ProjectionExec: expr=[avg(sum(store_sales.ss_sales_price)) PARTITION
BY [item.i_category, item.i_brand, store.s_store_name, store.s_company_name,
date_dim.d_year] ROWS BETWEEN UNBOUNDED PRECEDING AND UNBOUNDED FOLLOWING@8 > 0
as __common_expr_3, i_category@0 as i_category, i_brand@1 as i_brand,
s_store_name@2 as s_store_name, s_company_name@3 as s_company_name, d_year@4 as
d_year, d_moy@5 as d_moy, sum(store_sales.ss_sales_price)@6 as
sum(store_sales.ss_sales_price), rank() PARTITION BY [item.i_category,
item.i_brand, store.s_store_name, store.s_company_name] ORDER BY
[date_dim.d_year ASC NULLS LAST, date_dim.d_moy ASC NULLS LAST] RANGE BETWEEN
UNBOUNDED PRECEDING AND CURRENT ROW@7 as rank() PARTITION BY [item.i_category,
item.i_brand, store.s_store_name, store.s_company_name] ORDER BY
[date_dim.d_year ASC NULLS LAST, date_dim.d_moy ASC NULLS LAST] RANGE BETWEEN
UNBOUNDED PRECEDING AND CURRENT ROW, avg(sum(store_sales.ss_sales_price))
PARTITION BY [item.i_category, item.i_
brand, store.s_store_name, store.s_company_name, date_dim.d_year] ROWS BETWEEN
UNBOUNDED PRECEDING AND UNBOUNDED FOLLOWING@8 as
avg(sum(store_sales.ss_sales_price)) PARTITION BY [item.i_category,
item.i_brand, store.s_store_name, store.s_company_name, date_dim.d_year] ROWS
BETWEEN UNBOUNDED PRECEDING AND UNBOUNDED FOLLOWING]
WindowAggExec: wdw=[avg(sum(store_sales.ss_sales_price)) PARTITION
BY [item.i_category, item.i_brand, store.s_store_name, store.s_company_name,
date_dim.d_year] ROWS BETWEEN UNBOUNDED PRECEDING AND UNBOUNDED FOLLOWING:
Ok(Field { name: "avg(sum(store_sales.ss_sales_price)) PARTITION BY
[item.i_category, item.i_brand, store.s_store_name, store.s_company_name,
date_dim.d_year] ROWS BETWEEN UNBOUNDED PRECEDING AND UNBOUNDED FOLLOWING",
data_type: Float64, nullable: true, dict_id: 0, dict_is_ordered: false,
metadata: {} }), frame: WindowFrame { units: Rows, start_bound:
Preceding(UInt64(NULL)), end_bound: Following(UInt64(NULL)), is_causal: false }]
SortExec: expr=[i_category@0 ASC NULLS LAST, i_brand@1 ASC NULLS
LAST, s_store_name@2 ASC NULLS LAST, s_company_name@3 ASC NULLS LAST],
preserve_partitioning=[true]
CoalesceBatchesExec: target_batch_
```
state 10, looks like `WindowAggExec` is the one making issues
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