Support querying data from the Nebula graph database
This feature comes from the needs of commercial customers who have used Doris and Nebula, hoping to connect these two databases
changes mainly include:
* add New Graph Database JDBC Type
* Adapt the type and map the graph to the Doris type
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.
In clickhouse's 4.x version of jdbc, some UInt types use special Java types, so I adapted Doris's ClickHouse JDBC External
```
com.clickhouse.data.value.UnsignedByte;
com.clickhouse.data.value.UnsignedInteger;
com.clickhouse.data.value.UnsignedLong;
com.clickhouse.data.value.UnsignedShort;
```
* 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
This pr does three things:
1. Use Druid instead of HikariCP in JdbcClient
2. when download udf jar, add the name of the jar package after the local file name.
3. refactor some jdbcResource code
Currently, we use `UtFrameUtils` to start a FE server in the FE unit test.
Each test class has to do some initialization and clean up stuff with the JUnit4
`@BeforeClass` and `@AfterClass` annotation. It's redundant and boring.
Besides, almost all the APIs in `UtFrameUtils` has a `ConnectContext` parameter, which is not easy to use.
This PR proposes to use an inherit-manner, i.e., wrap all the common logic in base class `TestWithFeService`,
leveraging the
JUnit5 `@BeforeAll` and `@AfterAll` annotation to narrow down the setup and cleanup lifecycle to each test class instance.
At the same time, the derived concrete test class could directly use utility methods inherited from the base class,
without calling a util class and passing a `ConnectContext` argument.
`UtFrameUtils` and `DorisAssert` are marked as deprecated. We could remove these two classes
if this refactor works well for a time.
This feature is propsoed in [DSIP-1](https://cwiki.apache.org/confluence/display/DORIS/DSIP-001%3A+Java+UDF).
This PR support fixed-length input and output Java UDF. Phase I in DIP-1 is done after this PR.
To support Java UDF effeciently, I use no data copy in JNI call and all compute operations are off-heap in Java.
To achieve that, I use a UdfExecutor instead.
For users, a UDF class must have a public evaluate method.
