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Developer Guide

Table of contents

OpenSearch builds using Java 11 at a minimum and supports JDK 11, 14 and 17. This means you must have a JDK of supported version installed with the environment variable JAVA_HOME referencing the path to Java home for your JDK installation:

$ echo $JAVA_HOME
/Library/Java/JavaVirtualMachines/adoptopenjdk-11.jdk/Contents/Home

$ java -version
 openjdk version "11.0.1" 2018-10-16
 OpenJDK Runtime Environment 18.9 (build 11.0.1+13)
 OpenJDK 64-Bit Server VM 18.9 (build 11.0.1+13, mixed mode)

Here are the official instructions on how to set JAVA_HOME for different platforms: https://docs.oracle.com/cd/E19182-01/820-7851/inst_cli_jdk_javahome_t/.

For convenience, we recommend installing OpenSearch and OpenSearch Dashboards on your local machine. You can download the open source ZIP for each and extract them to a folder.

If you just want to have a quick look, you can also get an OpenSearch running with plugin installed by ./gradlew :opensearch-sql-plugin:run.

OpenSearch Dashboards is optional, but makes it easier to test your queries. Alternately, you can use curl from the terminal to run queries against the plugin.

Now you can check out the code from your forked GitHub repository and create a new branch for your bug fix or enhancement work:

$ git clone [email protected]:<your_account>/sql.git
$ git checkout -b <branch_name>

If there is update in main or you want to keep the forked repository long living, you can sync it by following the instructions: https://help.github.com/en/github/collaborating-with-issues-and-pull-requests/syncing-a-fork. Basically you just need to pull latest changes from upstream main once you add it for the first time:

#Merge to your local main
$ git fetch upstream
$ git checkout main
$ git merge upstream/main

#Merge to your branch if any
$ git checkout <branch_name>
$ git merge main

After getting the source code as well as OpenSearch and OpenSearch Dashboards, your workspace layout may look like this:

$ mkdir opensearch
$ cd opensearch
$ ls -la
total 32
drwxr-xr-x  7 user group^users 4096 Nov 21 12:59 .
drwxr-xr-x 19 user group^users 4096 Nov 21 09:44 ..
drwxr-xr-x 10 user group^users 4096 Nov  8 12:16 opensearch
drwxr-xr-x 14 user group^users 4096 Nov  8 12:14 opensearch-dashboards
drwxr-xr-x 16 user group^users 4096 Nov 15 10:59 sql

You can develop the plugin in your favorite IDEs such as Eclipse and IntelliJ IDEs. Before start making any code change, you may want to configure your IDEs. In this section, we show how to get IntelliJ up and running.

Although later version of JDK is required to build the plugin, the Java language level needs to be Java 8 for compatibility. Only in this case your plugin works with OpenSearch running against JDK 8. Otherwise it will raise runtime exception when executing new API from new JDK. In case your IDE doesn’t set it right, you may want to double check your project setting after import.

Firstly you need to add the following configuration to the JVM used by your IDE. For Intellij IDEA, it should be added to <OpenSearch installation>/config/jvm.options file. After configuring this, an agent in JVM will listen on the port when your OpenSearch bootstraps and wait for IDE debugger to connect. So you should be able to debug by setting up a “Remote Run/Debug Configuration”:

-agentlib:jdwp=transport=dt_socket,server=y,suspend=n,address=5005

Because our code is licensed under Apache 2, you need to add the following license header to all new source code files. To automate this whenever creating new file, you can follow instructions for your IDE:

/*
 * Licensed under the Apache License, Version 2.0 (the "License").
 * You may not use this file except in compliance with the License.
 * A copy of the License is located at
 *
 *    http://www.apache.org/licenses/LICENSE-2.0
 *
 * or in the "license" file accompanying this file. This file is distributed
 * on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either
 * express or implied. See the License for the specific language governing
 * permissions and limitations under the License.
 */

For example, here are the instructions for adding copyright profiles in IntelliJ IDEA.

Note that missing license header will be detected by Gradle license plugin and fails the build.

The plugin codebase is in standard layout of Gradle project:

.
├── CODE_OF_CONDUCT.md
├── CONTRIBUTING.md
├── LICENSE.TXT
├── NOTICE
├── README.md
├── THIRD-PARTY
├── build.gradle
├── config
│   └── checkstyle
├── docs
│   ├── attributions.md
│   ├── category.json
│   ├── dev
│   └── user
├── gradle.properties
├── gradlew
├── gradlew.bat
├── settings.gradle
├── common
├── core
├── doctest
├── opensearch
├── filesystem
├── prometheus
├── integ-test
├── legacy
├── plugin
├── protocol
├── ppl
├── sql
├── sql-cli
├── sql-jdbc
├── sql-odbc
└── workbench

Here are sub-folders (Gradle modules) for plugin source code:

  • plugin: OpenSearch plugin related code.
  • sql: SQL language processor.
  • ppl: PPL language processor.
  • core: core query engine.
  • opensearch: OpenSearch storage engine.
  • prometheus: Prometheus storage engine.
  • filesystem: File System storage engine (in development).
  • protocol: request/response protocol formatter.
  • common: common util code.
  • integ-test: integration and comparison test.

Here are other files and sub-folders that you are likely to touch:

  • build.gradle: Gradle build script.
  • config: only Checkstyle configuration files for now.
  • docs: documentation for developers and reference manual for users.
  • doc-test: code that run .rst docs in docs folder by Python doctest library.

Note that other related project code has already merged into this single repository together:

  • sql-cli: CLI tool for running query from command line.
  • sql-jdbc: JDBC driver.
  • sql-odbc: ODBC driver.
  • workbench: query workbench UI.

We’re integrated Checkstyle plugin into Gradle build: https://github.com/opensearch-project/sql/blob/main/config/checkstyle/google_checks.xml. So any violation will fail the build. You need to identify the offending code from Gradle error message and fix them and rerun the Gradle build. Here are the highlight of some Checkstyle rules:

Most of the time you just need to run ./gradlew build which will make sure you pass all checks and testing. While you’re developing, you may want to run specific Gradle task only. In this case, you can run ./gradlew with task name which only triggers the task along with those it depends on. Here is a list for common tasks:

Gradle Task Description
./gradlew assemble Generate jar and zip files in build/distributions folder.
./gradlew generateGrammarSource (Re-)Generate ANTLR parser from grammar file.
./gradlew compileJava Compile all Java source files.
./gradlew checkstyle Run all checks according to Checkstyle configuration.
./gradlew test Run all unit tests.
./gradlew :integ-test:integTest Run all integration test (this takes time).
./gradlew build Build plugin by run all tasks above (this takes time).

For integration test, you can use -Dtests.class “UT full path” to run a task individually. For example ./gradlew :integ-test:integTest -Dtests.class="*QueryIT".

To run the task above for specific module, you can do ./gradlew :<module_name>:task. For example, only build core module by ./gradlew :core:build.

Sometimes your Gradle build fails or timeout due to OpenSearch integration test process hung there. You can check this by the following commands:

#Check if multiple Gradle daemons started by different JDK.
#Kill unnecessary ones and restart if necessary.
$ ps aux | grep -i gradle
$ ./gradlew stop
$ ./gradlew start

#Check if OpenSearch integTest process hung there. Kill it if so.
$ ps aux | grep -i opensearch

#Clean and rebuild
$ ./gradlew clean
$ ./gradlew build

For test cases, you can use the cases in the following checklist in case you miss any important one and break some queries:

  • Functions
    • SQL functions
    • Special OpenSearch functions
  • Basic Query
    • SELECT-FROM-WHERE
    • GROUP BY & HAVING
    • ORDER BY
  • Alias
    • Table alias
    • Field alias
  • Complex Query
    • Subquery: IN/EXISTS
    • JOIN: INNER/LEFT OUTER.
    • Nested field query
    • Multi-query: UNION/MINUS
  • Other Statements
    • DELETE
    • SHOW
    • DESCRIBE
  • Explain
    • DSL for simple query
    • Execution plan for complex query like JOIN
  • Response format
    • Default
    • JDBC: You could set up DbVisualizer or other GUI.
    • CSV
    • Raw

For unit test:

  • Put your test class in the same package in src/test/java so you can access and test package-level method.
  • Make sure you are testing against the right abstraction with dependencies mocked. For example a bad practice is to create many classes by OpenSearchActionFactory class and write test cases on very high level. This makes it more like an integration test.

For integration test:

  • OpenSearch test framework is in use so an in-memory cluster will spin up for each test class.
  • You can only access the plugin and verify the correctness of your functionality via REST client externally.
  • Our homemade comparison test framework is used heavily to compare with other databases without need of assertion written manually. More details can be found in Testing.

Here is a sample for integration test for your reference:

public class XXXIT extends SQLIntegTestCase { // Extends our base test class

    @Override
    protected void init() throws Exception {
        loadIndex(Index.ACCOUNT); // Load predefined test index mapping and data
    }

    @Override
    public void testXXX() { // Test query against the index and make assertion
        JSONObject response = executeQuery("SELECT ...");
        Assert.assertEquals(6, getTotalHits(response));
    }
}

Finally thanks to JaCoCo library, you can check out the test coverage in <module_name>/build/reports/jacoco for your changes easily.

Sometime you want to deploy your changes to local OpenSearch cluster, basically there are couple of steps you need to follow:

  1. Re-assemble to generate plugin jar file with your changes.
  2. Replace the jar file with the new one in your workspace.
  3. Restart OpenSearch cluster to take it effect.

To automate this common task, you can prepare an all-in-one command for reuse. Below is a sample command for macOS:

./gradlew assemble && {echo y | cp -f build/distributions/opensearch-sql-1*0.jar <OpenSearch_home>/plugins/opensearch-sql} && {kill $(ps aux | awk '/[O]pensearch/ {print $2}'); sleep 3; nohup <OpenSearch_home>/bin/opensearch > ~/Temp/opensearch.log 2>&1 &}

Note that for the first time you need to create opensearch-sql folder and unzip build/distribution/opensearch-sql-xxxx.zip to it.

For new feature or big enhancement, it is worth document your design idea for others to understand your code better. There is already a docs/dev folder for all this kind of development documents.

Doc Generator

Currently the reference manual documents are generated from a set of special integration tests. The integration tests use custom DSL to build ReStructure Text markup with real query and result set captured and documented.

  1. Add a new template to src/test/resources/doctest/templates.
  2. Add a new test class as below with @DocTestConfig annotation specifying template and test data used.
  3. Run ./gradlew build to generate the actual documents into docs/user folder.

Sample test class:

@DocTestConfig(template = "interfaces/protocol.rst", testData = {"accounts.json"})
public class ProtocolIT extends DocTest {

    @Section(1)
    public void test() {
        section(
            title("A New Section"),
            description(
                "Describe what is the use of new functionality."
            ),
            example(
                description("Describe what is the use case of this example to show"),
                post("SELECT ...")
            )
        );
    }
}

Doctest

Python doctest library makes our document executable which keeps it up-to-date to source code. The doc generator aforementioned served as scaffolding and generated many docs in short time. Now the examples inside is changed to doctest gradually. For more details please read Doctest.

Backports

The Github workflow in backport.yml creates backport PRs automatically when the original PR with an appropriate label backport <backport-branch-name> is merged to main with the backport workflow run successfully on the PR. For example, if a PR on main needs to be backported to 1.x branch, add a label backport 1.x to the PR and make sure the backport workflow runs on the PR along with other checks. Once this PR is merged to main, the workflow will create a backport PR to the 1.x branch.