1. max compute partition prune,
we just support filter mc partitions by '='，it can filter just one partition
to support multiple partition filter and range operator('>','<', '>='..), the partition prune should be supported.
2. add max compute row count cache and partitionValues cache
3. add max compute regression case
1. check minio region, set default region if user region is not provided, and throw minio error msg
2. support read root path s3://bucket1
3. fix max compute public access
Use spark-bundle to read hudi data instead of using hive-bundle to read hudi data.
**Advantage** for using spark-bundle to read hudi data:
1. The performance of spark-bundle is more than twice that of hive-bundle
2. spark-bundle using `UnsafeRow` can reduce data copying and GC time of the jvm
3. spark-bundle support `Time Travel`, `Incremental Read`, and `Schema Change`, these functions can be quickly ported to Doris
**Disadvantage** for using spark-bundle to read hudi data:
1. More dependencies make hudi-dependency.jar very cumbersome(from 138M -> 300M)
2. spark-bundle only provides `RDD` interface and cannot be used directly
1. Fix MC jni scanner OOM
2. add the second datetime type for MC SDK timestamp
3. make s3 uri case insensitive by the way
4. optimize max compute scanner parallel model
Two optimizations:
1. Insert string bytes directly to remove decoding&encoding process.
2. Use native reader to read the hudi base file if it has no log file. Use `explain` to show how many splits are read natively.
The java-udf module has become increasingly large and difficult to manage, making it inconvenient to package and use as needed. It needs to be split into multiple sub-modules, such as : java-commom、java-udf、jdbc-scanner、hudi-scanner、 paimon-scanner.
Co-authored-by: lexluo <lexluo@tencent.com>
