Spark向Elasticsearch批量导入数据，出现重复记录问题的定位

看了下es-hadoop插件的源码：

发现ES导入数据重试情况的发生，除了在es.batch.write.retry.policy参数默认开启且es-hadoop插件向ES集群发送bulk写入请求接受到503响应码会重试3次之外。

本身执行http请求时，也会存在重试（hadoop/rest/NetworkClient.java）：

   public Response execute(Request request) {
        Response response = null;
        boolean newNode;
        do {
            SimpleRequest routedRequest = new SimpleRequest(request.method(), null, request.path(), request.params(), request.body());

            newNode = false;
            try {
                response = currentTransport.execute(routedRequest);
                ByteSequence body = routedRequest.body();
                if (body != null) {
                    stats.bytesSent += body.length();
                }
            } catch (Exception ex) {
                // configuration error - including SSL/PKI - bail out
                if (ex instanceof EsHadoopIllegalStateException) {
                    throw (EsHadoopException) ex;
                }
                // issues with the SSL handshake, bail out instead of retry, for security reasons
                if (ex instanceof javax.net.ssl.SSLException) {
                    throw new EsHadoopTransportException(ex);
                }
                // check for fatal, non-recoverable network exceptions
                if (ex instanceof BindException) {
                    throw new EsHadoopTransportException(ex);
                }

                if (log.isTraceEnabled()) {
                    log.trace(
                            String.format(
                                    "Caught exception while performing request [%s][%s] - falling back to the next node in line...",
                                    currentNode, request.path()), ex);
                }

                String failed = currentNode;

                failedNodes.put(failed, ex);

                newNode = selectNextNode();

                log.error(String.format("Node [%s] failed (%s); "
                        + (newNode ? "selected next node [" + currentNode + "]" : "no other nodes left - aborting..."),
                        failed, ex.getMessage()));

                if (!newNode) {
                    throw new EsHadoopNoNodesLeftException(failedNodes);
                }
            }
        } while (newNode);

        return response;
    }

当请求出现超时的情况时，es-hadoop插件会再请求一个ES节点发送写入请求。即导入插件认为当前插入节点超时了（默认是一分钟）就视为该节点不可用，就换下一个节点，其实是ES在一分钟内没有处理完插入任务。

将超时时间es.http.timeout参数调大之后，给ES留下充足的入库时间，就不会再发生这个问题了。