On Sun, 5 Mar 2023 at 18:27, zhangliyun <[email protected]> wrote:
> Hi all
>
>
> i have a spark sql , before in spark 2.4.2 it runs correctly, when i
> upgrade to spark 3.1.3, it has some problem.
>
> the sql
>
> ```
>
> select * from eds_rds.cdh_prpc63cgudba_pp_index_disputecasedetails_hourly
> where dt >= date_sub('${today}',30);
>
>
> ```
>
> it will load the data of past 30 days of table
> eds_rds.cdh_prpc63cgudba_pp_index_disputecasedetails_hourly, here
> today='2023-03-01'
>
>
> in spark2 i saw the physical plan the partition Filter is PartitionFilters:
> [isnotnull(dt#1461), (dt#1461 >= 2023-01-31)]
>
> +- *(4) FileScan parquet
> eds_rds.cdh_prpc63cgudba_pp_index_disputecasedetails_hourly[disputeid#1327,statuswork#1330,opTs#1457,trailSeqno#1459,trailRba#1460,dt#1461,hr#1462]
> Batched: true, Format: Parquet, Location:
> PrunedInMemoryFileIndex[gs://pypl-bkt-prd-row-std-gds-non-edw-tables/apps/risk/eds/eds_risk/eds_r...,
> PartitionCount: 805, PartitionFilters: [isnotnull(dt#1461), (dt#1461 >=
> 2023-01-31)], PushedFilters: [IsNotNull(disputeid)], ReadSchema:
> struct<disputeid:string,statuswork:string,opTs:string,trailSeqno:string,trailRba:string>
>
>
>
> in spark3 , i saw the physical plan , the partitionFilter is
> [isnotnull(dt#1602),
> (cast(dt#1602 as date) >= 19387)]
> ```
>
> (8) Scan parquet eds_rds.cdh_prpc63cgudba_pp_index_disputecasedetails_hourly
> Output [7]: [disputeid#1468, statuswork#1471, opTs#1598, trailSeqno#1600,
> trailRba#1601, dt#1602, hr#1603]
> Batched: true
> Location: InMemoryFileIndex
> [gs://pypl-bkt-prd-row-std-gds-non-edw-tables/apps/risk/eds/eds_risk/eds_rds/cdh/prpc63cgudba_pp_index_disputecasedetails/dt=2023-01-30/hr=00,
> ... 784 entries]
> PartitionFilters: [isnotnull(dt#1602), (cast(dt#1602 as date) >= 19387)]
> PushedFilters: [IsNotNull(disputeid)]
> ReadSchema:
> struct<disputeid:string,statuswork:string,opTs:string,trailSeqno:string,trailRba:string>
>
>
> ```
>
> here i want to ask why there is big difference in partitionFitler in
> spark2 and spark3, i guess most my spark configure is similar in spark2
> and spark3 to run the same sql
>
