parthchandra commented on PR #671:
URL: https://github.com/apache/datafusion-comet/pull/671#issuecomment-2234180553
> TPCDS Micro Benchmarks: Best Time(ms) Avg Time(ms)
Stdev(ms) Rate(M/s) Per Row(ns) Relative
>
------------------------------------------------------------------------------------------------------------------------
> add_many_decimals 20502 20648
208 14.0 71.2 1.0X
> add_many_decimals 20498 20544
65 14.1 71.2 1.0X
> add_many_decimals: Comet (Scan) 28143 28161
26 10.2 97.7 0.7X
> add_many_decimals: Comet (Scan, Exec) 19323 19497
246 14.9 67.1 1.1X
Just looking at this one case, with decimal fields and only scan enabled, we
are much slower. This is consistent with something I saw when working on the
parallel reader.
From a profiling run I saw that a potential bottleneck was
[BosonVector.getDecimal](https://github.com/apache/datafusion-comet/blob/7ac2fb9f6672fbb29c2e5de7e62b457efc0bfebf/common/src/main/java/org/apache/comet/vector/CometVector.java#L74)
which has an expensive creation of a BigInteger followed by an expensive
creation of a BigDecimal.
However, this path would be hit only for precision > 18 or if
`spark.comet.use.decimal128` was set to `true` (it is `false` by default).
Also, I'm not sure if there is a way to eliminate this though.
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