private void train()

in src/main/java/org/opensearch/knn/training/TrainingJobRunner.java [123:171]
43 lines of code
5 McCabe index (conditional complexity)

    private void train(TrainingJob trainingJob) {
        // Attempt to submit job to training thread pool. On failure, release the resources and serialize the failure.

        // Listener for update model after training index action
        ActionListener<IndexResponse> loggingListener = ActionListener.wrap(
                indexResponse -> logger.debug("[KNN] Model serialization update for \"" +
                        trainingJob.getModelId() + "\" was successful"),
                e -> {
                    logger.error("[KNN] Model serialization update for \"" + trainingJob.getModelId()  +
                            "\" failed: " + e.getMessage());
                    KNNCounter.TRAINING_ERRORS.increment();
                }
        );

        try {
            threadPool.executor(TRAIN_THREAD_POOL).execute(() -> {
                try {
                    trainingJob.run();
                    serializeModel(trainingJob, loggingListener, true);
                } catch (IOException e) {
                    logger.error("Unable to serialize model \"" + trainingJob.getModelId() + "\": " + e.getMessage());
                    KNNCounter.TRAINING_ERRORS.increment();
                } catch (Exception e) {
                    logger.error("Unable to complete training for \"" + trainingJob.getModelId() + "\": "
                            + e.getMessage());
                    KNNCounter.TRAINING_ERRORS.increment();
                } finally {
                    jobCount.decrementAndGet();
                    semaphore.release();
                }
            });
        } catch (RejectedExecutionException ree) {
            logger.error("Unable to train model \"" + trainingJob.getModelId() + "\": " + ree.getMessage());

            ModelMetadata modelMetadata = trainingJob.getModel().getModelMetadata();
            modelMetadata.setState(ModelState.FAILED);
            modelMetadata.setError("Training job execution was rejected. Node's training queue is at capacity.");

            try {
                serializeModel(trainingJob, loggingListener, true);
            } catch (IOException ioe) {
                logger.error("Unable to serialize the failure for model \"" + trainingJob.getModelId() + "\": " + ioe);
            } finally {
                jobCount.decrementAndGet();
                semaphore.release();
                KNNCounter.TRAINING_ERRORS.increment();
            }
        }
    }