This PR proposes mapping external catalog JSON types to String instead of JsonB in Apache Doris. This change is motivated by the realization that JDBC retrieves JSON data as a String JSON string, regardless of its storage format (Json(String) or Json(Binary)). Mapping to String streamlines data retrieval, simplifies write-backs, and ensures compatibility with all JSON(String) and JSON(Binary) functions, despite potentially misleading displays of JSON data as Strings in Doris. This approach avoids the performance overhead and complexity of converting each row of data from JsonB to String, making the process more efficient and elegant.
About Upgrade
To ensure query compatibility with existing Catalogs in the upgraded version,we currently still retain the capability to query external JSON types as JSONB. However, once you upgrade to the new version and either refresh the Catalog or create a new one, all external JSON types will be treated as Strings. To ensure consistent behavior,and possible future removal of support for JSON as JSONB query code, it is highly recommended that you manually refresh your Catalog as soon as possible after upgrading to the new version.
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.
In the old caching logic, we only used jdbcurl, user, and password as cache keys. This may cause the old link to be still used when replacing the jar package, so we should concatenate all the parameters required for the connection pool as the key.
1. Remove `doris_max_remote_scanner_thread_pool_thread_num`, use `doris_scanner_thread_pool_thread_num` only.
2. Set the default value `doris_scanner_thread_pool_thread_num` as `std::max(48, CpuInfo::num_cores() * 4)`
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. 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.
This commit overhauls the JDBC connector logic within our project, transitioning from the previous mechanism of fetching data through JNI calls for individual ResultSet items to a more efficient and unified approach using the VectorTable data structure.
Follow https://github.com/apache/doris/pull/25302, and use the unified jni framework to refactor java udaf.
This PR has removed the old interfaces to run java udf/udaf. Thanks to the ease of use of the new framework, the core code for modifying UDAF does not exceed 100 lines, and the logic is similar to that of UDF.
Use the unified jni framework to refactor java udf.
The unified jni framework takes VectorTable as the container to transform data between c++ and java, and hide the details of data format conversion.
In addition, the unified framework supports complex and nested types.
The performance of basic types remains consistent, with a 30% improvement in string types and an order of magnitude improvement in complex types.
Support complex types in jni framework, and successfully run end-to-end on hudi.
### How to Use
Other scanners only need to implement three interfaces in `ColumnValue`:
```
// Get array elements and append into values
void unpackArray(List<ColumnValue> values);
// Get map key array&value array, and append into keys&values
void unpackMap(List<ColumnValue> keys, List<ColumnValue> values);
// Get the struct fields specified by `structFieldIndex`, and append into values
void unpackStruct(List<Integer> structFieldIndex, List<ColumnValue> values);
```
Developers can take `HudiColumnValue` as an example.
* be scanner
- Upgrade avro to 1.11.2
fe
- Upgrade quartz to 2.5.0-rc1
- Upgrade maxcompute to 0.45-2-publish
- Binding avro-ipc to 1.11.2
* Binding hbase version to 2.5.5
binding nimbusds version to 9.35
Fix three bugs:
1. Hudi slice maybe has log files only, so `new Path(filePath)` will throw errors.
2. Hive column names are lowercase only, so match column names in ignore-case-mode.
3. Compatible with [Spark Datasource Configs](https://hudi.apache.org/docs/configurations/#Read-Options), so users can add `hoodie.datasource.merge.type=skip_merge` in catalog properties to skip merge logs files.
Add 2 metrics in jdbc scan node profile:
- `CallJniNextTime`: call get next from jdbc result set
- `ConvertBatchTime`: call convert jobject to columm block
Also fix a potential concurrency issue when init jdbc connection cache pool
1. Reduce the number of threads reading avro logs and keep the readers in a fixed thread pool.
2. Regularly cleaning the cached resolvers in the thread local map by reflection.
Sometimes, the partitions of a hive table may on different storage, eg, some is on HDFS, others on object storage(cos, etc).
This PR mainly changes:
1. Fix the bug of accessing files via cosn.
2. Add a new field `fs_name` in TFileRangeDesc
This is because, when accessing a file, the BE will get a hdfs client from hdfs client cache, and different file in one query
request may have different fs name, eg, some of are `hdfs://`, some of are `cosn://`, so we need to specify fs name
for each file, otherwise, it may return error:
`reason: IllegalArgumentException: Wrong FS: cosn://doris-build-1308700295/xxxx, expected: hdfs://[172.xxxx:4007](http://172.xxxxx:4007/)`
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.
