FelixYBW opened a new issue, #11534:
URL: https://github.com/apache/incubator-gluten/issues/11534
### Description
Using default parameters, Gluten parquet writer creates more rowgroup than
Spark, which leads to much worse perf than using Spark files
```
df.repartition(tbl_filenum[tbl]['part_cnt'],
tbl_filenum[tbl]['part']).write.mode("overwrite").format("parquet").option("compression",
"zstd").partitionBy(tbl_filenum[tbl]['part']).option('fs.s3a.committer.name',
'magic').save(f"s3a://presto-workload/{databasename}/{tbl}")
```
The table shows one stage of TPCDS q9 when reading spark and Gluten
generated store_sales table
Metric | spark generated | gluten generated | Difference
-- | -- | -- | --
Time of scan and filter | 18.8 min | 1.31 hours | 4.2x slower
I/O wait time | 2.09 hours | 10.09 hours | 4.8x slower
Time of scan | 1.85 hours | 8.84 hours | 4.8x slower
Page load time | 14.0 min | 1.25 hours | 5.4x slower
Data source read time | 4.8 min | 21.6 min | 4.5x slower
Storage read bytes | 31.5 GiB | 34.7 GiB | 10% more data read
**Size of files read** | 240.7 GiB | 256.6 GiB | 6.6% larger
Peak memory | 16.0 GiB | 14.1 GiB | 12% less memory used
**Row groups processed** | **2,666** | **8,727** | 3.3x more row groups
Memory allocations | 17,584,444 | 14,466,793 | 18% fewer allocations
**Preloaded splits** | 1,585 | 1,710 | 8% more preloaded
### Gluten version
None
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