jinwenjie123

I also encountered similar issue when I conducted the test for running spark3.4.4 in AWS. I fixed it by changing to spark3.4.3 since it looks like the issue is caused...

> [@jinwenjie123](https://github.com/jinwenjie123) I would recommend starting off by using a pre-built JAR which contains native binaries for multiple architectures. > > https://datafusion.apache.org/comet/user-guide/installation.html#using-a-published-jar-file I will give it a try. Many thanks...

Hi @andygrove , Thanks for your previous suggestions. However, when I use the precompiled JARs, I encounter a `GLIBC_2.27 not found` error. I modified the [Dockerfile](https://github.com/apache/datafusion-comet/blob/main/dev/release/comet-rm/Dockerfile) to use `amazon_linux:2 environment`,...

@parthchandra Looks like using ubuntu 16.04 dose not work since the dependencies will not compile successfully. I tried to use the zigbuild, at least `cd native && cargo zigbuild --target...

I tried to run the benchmark for [TPCH_Q1](https://github.com/apache/spark/blob/master/sql/core/src/test/resources/tpch/q1.sql) query, but it looks like it dose not provide much improvement by adding comet. Maybe due to the following error: `org.apache.comet.serde.QueryPlanSerde Comet...

> > `org.apache.comet.serde.QueryPlanSerde Comet native execution is disabled due to: unsupported Spark partitioning: org.apache.spark.sql.catalyst.plans.physical.RangePartitioning` > > `org.apache.comet.serde.QueryPlanSerde Comet native execution is disabled due to: unsupported Spark data type: MapType(StringType,StringType,true)` >...

Hi @andygrove May I ask why we decide not support RangePartitioning ? and will it be supported in the near future ? Thanks