Document usage of backoff policy in BulkProcessor
With this commit we update the documentation to explain the new backoff feature in BulkProcessor. Relates to #14620.
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@ -47,6 +47,7 @@ To use it, first create a `BulkProcessor` instance:
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[source,java]
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--------------------------------------------------
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import org.elasticsearch.action.bulk.BackoffPolicy;
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import org.elasticsearch.action.bulk.BulkProcessor;
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import org.elasticsearch.common.unit.ByteSizeUnit;
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import org.elasticsearch.common.unit.ByteSizeValue;
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@ -73,6 +74,8 @@ BulkProcessor bulkProcessor = BulkProcessor.builder(
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.setBulkSize(new ByteSizeValue(1, ByteSizeUnit.GB)) <6>
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.setFlushInterval(TimeValue.timeValueSeconds(5)) <7>
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.setConcurrentRequests(1) <8>
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.setBackoffPolicy(
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BackoffPolicy.exponentialBackoff(TimeValue.timeValueMillis(100), 3)) <9>
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.build();
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--------------------------------------------------
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<1> Add your elasticsearch client
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@ -86,6 +89,10 @@ BulkProcessor bulkProcessor = BulkProcessor.builder(
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<7> We want to flush the bulk every 5 seconds whatever the number of requests
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<8> Set the number of concurrent requests. A value of 0 means that only a single request will be allowed to be
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executed. A value of 1 means 1 concurrent request is allowed to be executed while accumulating new bulk requests.
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<9> Set a custom backoff policy which will initially wait for 100ms, increase exponentially and retries up to three
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times. A retry is attempted whenever one or more bulk item requests have failed with an `EsRejectedExecutionException`
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which indicates that there were too little compute resources available for processing the request. To disable backoff,
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pass `BackoffPolicy.noBackoff()`.
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Then you can simply add your requests to the `BulkProcessor`:
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@ -101,6 +108,7 @@ By default, `BulkProcessor`:
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* sets bulkSize to `5mb`
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* does not set flushInterval
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* sets concurrentRequests to 1
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* sets backoffPolicy to an exponential backoff with 8 retries and a start delay of 50ms. The total wait time is roughly 5.1 seconds.
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When all documents are loaded to the `BulkProcessor` it can be closed by using `awaitClose` or `close` methods:
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