Before this PR, Paimon has created the schema of `VectorTable` by accessing meta information. However, once the schema of `VectorTable` in java is not same as `Block` in c++, BE will crashed, and there is no good way to troubleshoot errors.
1. Do not use FATAL log when jni encounter error, to avoid crash.
2. Fix NPE when closing PaimonReader, the reader may not be assigned if PaimonReader open failed.
1.support filesystem metastore
2.support predicate and project when split
3.fix partition table query error
todo: Now you need to manually put paimon-s3-0.4.0-incubating.jar in be/lib/java_extensions when use s3 filesystem
doc pr: #21966
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
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>
