There are two choices for batch data ingestion to your Druid cluster, you can use the [Indexing service](Indexing-Service.html) or you can use the `HadoopDruidIndexer`.
The [Indexing service](Indexing-Service.html) is a set of nodes that can run as part of your Druid cluster and can accomplish a number of different types of indexing tasks. Even if all you care about is batch indexing, it provides for the encapsulation of things like the [metadata store](Metadata-storage.html) that is used for segment metadata and other things, so that your indexing tasks do not need to include such information. The indexing service was created such that external systems could programmatically interact with it and run periodic indexing tasks. Long-term, the indexing service is going to be the preferred method of ingesting data.
The `HadoopDruidIndexer` runs hadoop jobs in order to separate and index data segments. It takes advantage of Hadoop as a job scheduling and distributed job execution platform. It is a simple method if you already have Hadoop running and don’t want to spend the time configuring and deploying the [Indexing service](Indexing-Service.html) just yet.
Is a type of data loader that expects data to be laid out in a specific path format. Specifically, it expects it to be segregated by day in this directory format `y=XXXX/m=XX/d=XX/H=XX/M=XX/S=XX` (dates are represented by lowercase, time is represented by uppercase).
This is a specification of the properties that tell the job how to update metadata such that the Druid cluster will see the output segments and load them.
These properties should parrot what you have configured for your [Coordinator](Coordinator.html).
### TuningConfig
The tuningConfig is optional and default parameters will be used if no tuningConfig is specified.
|Field|Type|Description|Required|
|-----|----|-----------|--------|
|workingPath|String|the working path to use for intermediate results (results between Hadoop jobs).|no (default == '/tmp/druid-indexing')|
|version|String|The version of created segments.|no (default == datetime that indexing starts at)|
|leaveIntermediate|leave behind files in the workingPath when job completes or fails (debugging tool).|no (default == false)|
|partitionsSpec|Object|a specification of how to partition each time bucket into segments, absence of this property means no partitioning will occur.More details below.|no (default == 'hashed'|
|maxRowsInMemory|Integer|The number of rows to aggregate before persisting. This number is the post-aggregation rows, so it is not equivalent to the number of input events, but the number of aggregated rows that those events result in. This is used to manage the required JVM heap size.|no (default == 5 million)|
|cleanupOnFailure|Boolean|Cleans up intermediate files when the job fails as opposed to leaving them around for debugging.|no (default == true)|
|overwriteFiles|Boolean|Override existing files found during indexing.|no (default == false)|
|ignoreInvalidRows|Boolean|Ignore rows found to have problems.|no (default == false)|
|jobProperties|Object|a map of properties to add to the Hadoop job configuration.|no (default == null)|
|targetPartitionSize|target number of rows to include in a partition, should be a number that targets segments of 500MB\~1GB.|either this or numShards|
|numShards|specify the number of partitions directly, instead of a target partition size. Ingestion will run faster, since it can skip the step necessary to select a number of partitions automatically.|either this or targetPartitionSize|
|assumeGrouped|assume input data has already been grouped on time and dimensions. Ingestion will run faster, but can choose suboptimal partitions if the assumption is violated.|no|
Batch ingestion for the indexing service is done by submitting an [Index Task](Tasks.html) (for datasets <1G)ora [Hadoop Index Task](Tasks.html).Theindexingservicecanbestartedbyissuing:
|pathSpec|Object|a specification of where to pull the data in from|yes|
### TuningConfig
The tuningConfig is optional and default parameters will be used if no tuningConfig is specified. This is the same as the tuningConfig for the standalone Hadoop indexer. See above for more details.
The Hadoop Index Config submitted as part of an Hadoop Index Task is identical to the Hadoop Index Config used by the `HadoopBatchIndexer` except that three fields must be omitted: `segmentOutputPath`, `workingPath`, `updaterJobSpec`. The Indexing Service takes care of setting these fields internally.
If the task succeeds, you should see in the logs of the indexing service:
```
2013-10-16 16:38:31,945 INFO [pool-6-thread-1] io.druid.indexing.overlord.exec.TaskConsumer - Task SUCCESS: HadoopIndexTask...
```
Having Problems?
----------------
Getting data into Druid can definitely be difficult for first time users. Please don't hesitate to ask questions in our IRC channel or on our [google groups page](https://groups.google.com/forum/#!forum/druid-development).
