[[bulk]] == Bulk API The bulk API allows one to index and delete several documents in a single request. Here is a sample usage: [source,java] -------------------------------------------------- import static org.elasticsearch.common.xcontent.XContentFactory.*; BulkRequestBuilder bulkRequest = client.prepareBulk(); // either use client#prepare, or use Requests# to directly build index/delete requests bulkRequest.add(client.prepareIndex("twitter", "tweet", "1") .setSource(jsonBuilder() .startObject() .field("user", "kimchy") .field("postDate", new Date()) .field("message", "trying out Elasticsearch") .endObject() ) ); bulkRequest.add(client.prepareIndex("twitter", "tweet", "2") .setSource(jsonBuilder() .startObject() .field("user", "kimchy") .field("postDate", new Date()) .field("message", "another post") .endObject() ) ); BulkResponse bulkResponse = bulkRequest.execute().actionGet(); if (bulkResponse.hasFailures()) { // process failures by iterating through each bulk response item } -------------------------------------------------- [float] == Using Bulk Processor The `BulkProcessor` class offers a simple interface to flush bulk operations automatically based on the number or size of requests, or after a given period. To use it, first create a `BulkProcessor` instance: [source,java] -------------------------------------------------- import org.elasticsearch.action.bulk.BulkProcessor; BulkProcessor bulkProcessor = BulkProcessor.builder( client, <1> new BulkProcessor.Listener() { @Override public void beforeBulk(long executionId, BulkRequest request) { ... } <2> @Override public void afterBulk(long executionId, BulkRequest request, BulkResponse response) { ... } <3> @Override public void afterBulk(long executionId, BulkRequest request, Throwable failure) { ... } <4> }) .setBulkActions(10000) <5> .setBulkSize(new ByteSizeValue(1, ByteSizeUnit.GB)) <6> .setFlushInterval(TimeValue.timeValueSeconds(5)) <7> .setConcurrentRequests(1) <8> .build(); -------------------------------------------------- <1> Add your elasticsearch client <2> This method is called just before bulk is executed. You can for example see the numberOfActions with `request.numberOfActions()` <3> This method is called after bulk execution. You can for example check if there was some failing requests with `response.hasFailures()` <4> This method is called when the bulk failed and raised a `Throwable` <5> We want to execute the bulk every 10 000 requests <6> We want to flush the bulk every 1gb <7> We want to flush the bulk every 5 seconds whatever the number of requests <8> Set the number of concurrent requests. A value of 0 means that only a single request will be allowed to be executed. A value of 1 means 1 concurrent request is allowed to be executed while accumulating new bulk requests. Then you can simply add your requests to the `BulkProcessor`: [source,java] -------------------------------------------------- bulkProcessor.add(new IndexRequest("twitter", "tweet", "1").source(/* your doc here */)); bulkProcessor.add(new DeleteRequest("twitter", "tweet", "2")); -------------------------------------------------- By default, `BulkProcessor`: * sets bulkActions to `1000` * sets bulkSize to `5mb` * does not set flushInterval * sets concurrentRequests to 1 When all documents are loaded to the `BulkProcessor` it can be closed by using `awaitClose` or `close` methods: [source,java] -------------------------------------------------- bulkProcessor.awaitClose(10, TimeUnit.MINUTES); -------------------------------------------------- or [source,java] -------------------------------------------------- bulkProcessor.close(); -------------------------------------------------- Both methods flush any remaining documents and disable all other scheduled flushes if they were scheduled by setting `flushInterval`. If concurrent requests were enabled the `awaitClose` method waits for up to the specified timeout for all bulk requests to complete then returns `true`, if the specified waiting time elapses before all bulk requests complete, `false` is returned. The `close` method doesn't wait for any remaining bulk requests to complete and exists immediately.