132 lines
5.5 KiB
Plaintext
132 lines
5.5 KiB
Plaintext
[[java-docs-bulk]]
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=== Bulk API
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The bulk API allows one to index and delete several documents in a
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single request. Here is a sample usage:
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[source,java]
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--------------------------------------------------
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import static org.elasticsearch.common.xcontent.XContentFactory.*;
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BulkRequestBuilder bulkRequest = client.prepareBulk();
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// either use client#prepare, or use Requests# to directly build index/delete requests
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bulkRequest.add(client.prepareIndex("twitter", "tweet", "1")
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.setSource(jsonBuilder()
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.startObject()
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.field("user", "kimchy")
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.field("postDate", new Date())
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.field("message", "trying out Elasticsearch")
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.endObject()
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)
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);
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bulkRequest.add(client.prepareIndex("twitter", "tweet", "2")
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.setSource(jsonBuilder()
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.startObject()
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.field("user", "kimchy")
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.field("postDate", new Date())
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.field("message", "another post")
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.endObject()
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)
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);
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BulkResponse bulkResponse = bulkRequest.get();
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if (bulkResponse.hasFailures()) {
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// process failures by iterating through each bulk response item
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}
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--------------------------------------------------
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[[java-docs-bulk-processor]]
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=== Using Bulk Processor
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The `BulkProcessor` class offers a simple interface to flush bulk operations automatically based on the number or size
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of requests, or after a given period.
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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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import org.elasticsearch.common.unit.TimeValue;
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BulkProcessor bulkProcessor = BulkProcessor.builder(
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client, <1>
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new BulkProcessor.Listener() {
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@Override
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public void beforeBulk(long executionId,
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BulkRequest request) { ... } <2>
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@Override
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public void afterBulk(long executionId,
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BulkRequest request,
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BulkResponse response) { ... } <3>
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@Override
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public void afterBulk(long executionId,
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BulkRequest request,
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Throwable failure) { ... } <4>
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})
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.setBulkActions(10000) <5>
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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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<2> This method is called just before bulk is executed. You can for example see the numberOfActions with
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`request.numberOfActions()`
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<3> This method is called after bulk execution. You can for example check if there was some failing requests
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with `response.hasFailures()`
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<4> This method is called when the bulk failed and raised a `Throwable`
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<5> We want to execute the bulk every 10 000 requests
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<6> We want to flush the bulk every 1gb
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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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[source,java]
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--------------------------------------------------
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bulkProcessor.add(new IndexRequest("twitter", "tweet", "1").source(/* your doc here */));
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bulkProcessor.add(new DeleteRequest("twitter", "tweet", "2"));
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--------------------------------------------------
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By default, `BulkProcessor`:
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* sets bulkActions to `1000`
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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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[source,java]
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--------------------------------------------------
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bulkProcessor.awaitClose(10, TimeUnit.MINUTES);
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--------------------------------------------------
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or
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[source,java]
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--------------------------------------------------
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bulkProcessor.close();
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--------------------------------------------------
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Both methods flush any remaining documents and disable all other scheduled flushes if they were scheduled by setting
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`flushInterval`. If concurrent requests were enabled the `awaitClose` method waits for up to the specified timeout for
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all bulk requests to complete then returns `true`, if the specified waiting time elapses before all bulk requests complete,
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`false` is returned. The `close` method doesn't wait for any remaining bulk requests to complete and exits immediately.
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