bhasudha commented on issue #1798:
URL: https://github.com/apache/hudi/issues/1798#issuecomment-654251026
> Document
>
> ```
> val hudiIncQueryDF = spark
> .read()
> .format("org.apache.hudi")
> .option(DataSourceReadOptions.QUERY_TYPE_OPT_KEY(),
DataSourceReadOptions.QUERY_TYPE_SNAPSHOT_OPT_VAL())
> .load(tablePath + "/*") //The number of wildcard asterisks here must
be one greater than the number of partition
> ```
>
> we have path like data/YYYY/MM/DD and when try as document mentioned
>
> ```
> spark.read.format("org.apache.hudi").load("s3://test/data/*/*/*/*")
> // 4000+ files cost 60s
> scala> res8.count
> res9: Long = 313589086
> ```
>
> but when we test with
>
> ```
> spark.read.format("org.apache.hudi").load("s3://test/data/*/*/*")
> // 600+ files cost 10s
> scala> res10.count
> res11: Long = 313589086
> ```
>
> result is the same, but with `s3://test/data/*/*/*` we could have much
more fast speed.
> and basically the the more file count the path included, the much more
huge difference the time cost will be....
>
> Is there any concern with using the path with less level of parquet file?
@zherenyu831 Thanks for reaching out. Do you mind sharing what was your
query on the table?
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