![]() Step 4 and 5) As we can see we have used the upsert method of the UpdateRequest class. Step 3) Using the builder.field() of XContentBuilder command as explained above. Note that these keys are also our field names in the employee_index mappings we defined earlier. Step 2) Using the method map.keySet() to get Keys from the Map. ![]() Step 1) Using Jackson’s ObjectMapper’s convertValue method to convert the employee object into a Java Map ( Key -> Value pairs). Let us understand the important aspects to Ingest Data into ES Index(using the code snippet mentioned above): Rather the ingestions can go an “Asynchronously” and the required complications/error arising shall be handled by the BulkListener itself.įinally, for each employee object in our employeeList, lets simply add them to the bulkprocessor object by executing the following: The client.bulkAsync() method shows that the High Level Rest Client need not wait for a BulkResponse object to be returned after indexing/updating a batch of documents and then go ahead with updating the next batch of documents. Step 5) Here is where we actually build our BulkProcessor by invoking the build() method. Step 4) This method is called when a BulkRequest failed Step 3) This method is called after each execution of a BulkRequest Step 2) This method is called before each execution of a BulkRequest Step 1) Created a BulkProcessor.listener which is called before and after every BulkRequest execution or when a BulkRequest failed, where BulkRequest Class is used by JHLC to insert/update multiple documents in one go. Let us understand the important aspects to create a BulkProcessor (using the code snippet mentioned above): The BulkProcessor simplifies the usage of the Bulk API by providing a utility class that allows index(insert) and update operations to be transparently executed as they are added to the processor. JHLC comes to the rescue again by providing a class called the BulkProcessor that can be easily imported and utilized. It is quite evident that right now, we have a pretty large dataset. endObject() Ingestion API using JHLC’s Bulk APIs XContentBuilder builder = jsonBuilder().startObject() Using XContentBuilder’s builder object, we can build the JSON document that is to be indexed, using the following command: XContentBuilder is a built-in ElasticSearch Helper that is used to generate JSON documents. So go ahead and read the cleaned dataset line by line in Java and deserialize Java objects from JSON using ObjectMapper’s readValue method and append them to a list of Employee Objects using the following commands: Employee employee = mapper.readValue(line, Employee.class) employeeList.add(employee) Generating JSON from Java objects is also referred to as to serialize Java objects into JSON. ![]() The Jackson ObjectMapper can also create JSON from Java objects. Parsing JSON into Java objects is also referred to as to deserialize Java objects from JSON. The Jackson ObjectMapper can parse JSON from a string, stream or file, and create a Java object representing the parsed JSON. ObjectMapper class is the simplest way to parse JSON with Jackson.
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