bind netty-version to 4.1.89-final
bind jettison to 1.5.4
upgrade hadoop version to 3.3.5
upgrade range-plugins-common to 2.4.0
bind bcprov-jdk15on to 2.4.0
upgrade and bind woodstox to 6.5.1
upgrade and bind kerby to 2.0.3
upgrade hudi to 0.13.0
upgrade parquet to 1.13.0
upgrade maven-source-plugin to 3.2.1
upgrade maven-assembly-plugin to 3.3.0
upgrade maven-javadoc-plugin to 3.3.2
upgrade maven-shade-plugin to 3.3.4
upgrade maven-clean-plugin to 3.1.0
Remove meaningless plugins
Optimize doris maven path
Unify the Java modules for management in fe
`Hive 3` uses the `thrift-0.9.3` package, and `Doris` uses the `thrift-0.16.0` package.
These two packages are not compatible, so we use the `hive-sahde` package to manage hive dependencies
in a unified way. This jar package renames the `thrift` class , so the problem of conflict can be resolved.
* Upgrade log4j to 2.X
- binding log4j version to 2.18.0
- used log4j-1.2-api complete smooth upgrade
* Upgrade filerupload to 1.5
* Upgrade commons-io to 2.7
* Upgrade commons-compress to 1.22
* Upgrade gson to 2.8.9
* Upgrade guava to 30.0-jre
* Binding jackson version to 2.14.2
* Upgrade netty-all to 4.1.89.final
* Upgrade protobuf to 3.21.12
* Upgrade kafka-clints to 3.4.0
* Upgrade calcite version to 1.33.0
* Upgrade aws-java-sdk to 1.12.302
* Upgrade hadoop to 3.3.4
* Upgrade zookeeper to 3.4.14
* Binding tomcat-embed-core to 8.5.86
* Upgrade apache parent pom to 25
* Use hive-exec-core as a hive dependency, add the missing jar-hive-serde separately
* Basic public dependencies are extracted to parent dependencies
* Use jackson uniformly as the basic json tool
* Remove springloaded, spring-boot-devtools has the same functionality
* Modify the spark-related dependency scope to provide, which should be provided at runtime
1. Spark dpp
Move `DppResult` and `EtlJobConfig` to sparkdpp package in `fe-common` module.
So taht `fe-core` is longer depends on `spark-dpp` module, so that the `spark-dpp.jar`
will not be moved into `fe/lib`, which reduce the size of FE output.
2. Modify start_fe.sh
Modify the CLASSPATH to make sure that doris-fe.jar is at front, so that
when loading classes with same qualified name, it will be got from doris-fe.jar firstly.
3. Upgrade hadoop and hive version
hadoop: 2.10.2 -> 3.3.3
hive: 2.3.7 -> 3.1.3
4. Override the IHiveMetastoreClient implementations from dependency
`ProxyMetaStoreClient.java` for Aliyun DLF.
`HiveMetaStoreClient.java` for origin Apache Hive metastore.
Because I need to modified some of their method to make them compatible with
different version of Hive.
5. Exclude some unused dependencies to reduce the size of FE output
Now it is only 370MB (Before is 600MB)
6. Upgrade aws-java-sdk version to 1.12.31
7. Support AWS Glue Data Catalog
8. Remove HudiScanNode(no longer support)
Hive Bitmap UDF provides UDFs for generating bitmap and bitmap operations in hive tables.
The bitmap in Hive is exactly the same as the Doris bitmap.
The bitmap in Hive can be imported into Doris through spark bitmap load.
