backport: #35690
`PropertyConverter.setS3FsAccess` has add customized s3 providers:
```
public static final List<String> AWS_CREDENTIALS_PROVIDERS = Arrays.asList(
DataLakeAWSCredentialsProvider.class.getName(),
TemporaryAWSCredentialsProvider.class.getName(),
SimpleAWSCredentialsProvider.class.getName(),
EnvironmentVariableCredentialsProvider.class.getName(),
IAMInstanceCredentialsProvider.class.getName());
```
And these providers are set as configuration value of
`fs.s3a.aws.credentials.provider`, which will be used as configuration
to build s3 reader in JNI readers. However,
`DataLakeAWSCredentialsProvider` is in `fe-core`, that is not dependent
by JNI readers, so we have to move s3 providers to `fe-common'.
The avro-scanner-jar package is reduced from 204M to 160M.
Hadoop-related dependencies in the original avro pom are directly packaged into a jar package, resulting in a jar volume of 200M. Now since there is already a hadoop jar package environment in be lib, it can be directly referenced.
This pr fixes two issues:
1. when using s3 TVF to query files in AVRO format, due to the change of `TFileType`, the originally queried `FILE_S3 ` becomes `FILE_LOCAL`, causing the query failed.
2. currently, both parameters `s3.virtual.key` and `s3.virtual.bucket` are removed. A new `S3Utils` in jni-avro to parse the bucket and key of s3.
The purpose of doing this operation is mainly to unify the parameters of s3.
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
