/**
 * A non-blocking interface to a web socket. Use the [factory][WebSocket.Factory] to create
 * instances; usually this is [OkHttpClient].
 *
 * ## Web Socket Lifecycle
 *
 * Upon normal operation each web socket progresses through a sequence of states:
 *
 *  * **Connecting:** the initial state of each web socket. Messages may be enqueued but they won't
 *    be transmitted until the web socket is open.
 *

is added to the map.
Conversely, when comparing types, a known type argument
(a type argument for which a map entry already exists)
takes the place of its corresponding type parameter.
As type inference progresses, the map is populated more and more
until all equations have been considered, or until unification fails.
Type inference succeeds if no unification step fails and the map has
an entry for each type parameter.
</p>

import org.opensearch.index.query.QueryBuilder;
import org.opensearch.index.query.QueryBuilders;

/**
 * Helper class for managing data crawling operations in Fess.
 * This class coordinates the execution of data store crawling processes,
 * managing multiple concurrent crawling threads and handling the indexing
 * of crawled documents into the search engine.
 *
 * <p>The DataIndexHelper supports:</p>
 * <ul>

     * Continuously processes crawled documents from the data service, transforms them,
     * and updates the search index until crawling is finished and all documents are processed.
     *
     * <p>The method performs the following operations in a loop:
     * <ul>
     * <li>Retrieves access results from the data service</li>
     * <li>Processes each document through transformers</li>

* Others...

## Replication - Processes and Memory { #replication-processes-and-memory }

With a FastAPI application, using a server program like the `fastapi` command that runs Uvicorn, running it once in **one process** can serve multiple clients concurrently.

But in many cases, you will want to run several worker processes at the same time.

### Multiple Processes - Workers { #multiple-processes-workers }

    margin-bottom: 0.75rem;
}

.progress-step {
    display: flex;
    flex-direction: column;
    align-items: center;
    padding: 0.5rem;
    min-width: 70px;
    opacity: 0.4;
    transition: all 0.3s ease;
}

.progress-step.active {
    opacity: 1;
}

.progress-step.completed {
    opacity: 0.7;
}

.progress-step .step-icon {
    width: 32px;
    height: 32px;

* Restarts
* **Replication (the number of processes running)**
* Memory
* Previous steps before starting

Up to this point, with all the tutorials in the docs, you have probably been running a **server program**, for example, using the `fastapi` command, that runs Uvicorn, running a **single process**.

        try {
            // Start multiple processes
            processHelper.startProcess(sessionId1, cmdList, pbCall);
            processHelper.startProcess(sessionId2, cmdList, pbCall);

            assertTrue(processHelper.isProcessRunning());

            // Wait a bit for the processes to start
            Thread.sleep(50);

            // Destroy all processes
            processHelper.destroy();

### Containers with Multiple Processes and Special Cases { #containers-with-multiple-processes-and-special-cases }

Of course, there are **special cases** where you could want to have **a container** with several **Uvicorn worker processes** inside.

In those cases, you can use the `--workers` command line option to set the number of workers that you want to run:

## Decision

1. The Gradle distribution will never include a Java runtime.
   Instead, Gradle will leverage Java toolchains for the Daemon and worker processes.
2. The Gradle Daemon, Worker processes, and Tooling API client will continue to support running on different Java versions during a single Gradle invocation.
   The exact versions supported will be determined by the Gradle version.