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h2. HDFS Component
*Available as of Camel 2.8*

The *hdfs* component enables you to read and write messages from/to an HDFS file system. HDFS is the distributed file system at the heart of [Hadoop|http://hadoop.apache.org].
It can only be built using JDK1.6 or later because  this is a strict requirement for Hadoop itself.
This component is hosted at http://github.com/dgreco/camel-hdfs. We decided to put it temporarily on this [github|http://www.github.com] because currently Camel is being built and tested using JDK1.5 and for this reason we couldn't put that component into the Camel official distribution. Hopefully, as soon Camel will allow to use JDK1.6 for building and testing we will put it into the trunk.
This component is developed and tested using the latest Camel snapshot, but it should work seamlessly with the latest Camel GA version (at the time of writing 2.1.0)
Maven users will need to add the following dependency to their {{pom.xml}} for this component:
{code:xml}
<dependency>
    <groupId>org.apache.camel</groupId>
    <artifactId>camel-hadoop</artifactId>
    <version>x.x.x</version>
    <!-- use the same version as your Camel core version -->
</dependency>
{code}

h3. URI format

{code}
hdfs://hostname[:port][/path][?options]
{code}

You can append query options to the URI in the following format, {{?option=value&option=value&...}}
The path is treated in the following way:
# as a consumer, if it's a file, it just reads the file, otherwise if it represents a directory it scans all the file under the path satisfying the configured pattern. All the files under that directory must be of the same type.
# as a producer, if at least one split strategy is defined, the path is considered a directory and under that directory the producer creates a different file per split named seg0, seg1, seg2, etc.

h3. Options
{div:class=confluenceTableSmall}
|| Name || Default Value || Description ||
| {{overwrite}} | {{true}} | The file can be overwritten |
| {{bufferSize}} | {{4096}} | The buffer size used by HDFS  |
| {{replication}} | {{3}} | The HDFS replication factor  |
| {{blockSize}} | {{67108864}} | The size of the HDFS blocks  |
| {{fileType}} | {{NORMAL_FILE}} | It can be SEQUENCE_FILE,
                                   MAP_FILE, ARRAY_FILE, or
                                   BLOOMMAP_FILE, see Hadoop |
| {{fileSystemType}} | {{HDFS}} | It can be LOCAL for local filesystem  |
| {{keyType}} | {{NULL}} | The type for the key in case of
                           sequence or map files. See below.  |
| {{valueType}} | {{TEXT}} | The type for the key in case of
                             sequence or map files. See below.  |
| {{splitStrategy}} | | A string describing the strategy on 
                        how to split the file based on different
                        criteria. See below.  |
| {{openedSuffix}} | {{opened}} | When a file is opened for reading/
                                  writing the file is renamed with this
                                  suffix to avoid to read it during the
                                  writing phase. |
| {{readSuffix}} | {{read}} | Once the file has been read is
                              renamed with this suffix to avoid to
                              read it again.  |
| {{initialDelay}} | {{0}} | For the consumer, how much to wait (milliseconds)
                             before to start scanning the directory.  |
| {{delay}} | {{0}} | The interval (milliseconds) between the directory
                      scans. |
| {{pattern}} | {{*}} | The pattern used for scanning the
                        directory  |
| {{chunkSize}} | {{4096}} | When reading a normal file, this is split   
                             into chunks producing a message per
                             chunk  chunk. |
{div}

h4. KeyType and ValueType
* NULL it means that the key or the value is absent
* BYTE for writing a byte, the java Byte class is mapped into a BYTE
* BYTES for writing a sequence of bytes. It maps the java ByteBuffer class
* INT for writing java integer     
* FLOAT for writing java float
* LONG for writing java long
* DOUBLE for writing java double
* TEXT for writing java strings

BYTES is also used with everything else, for example, in Camel a file is sent around as an InputStream, int this case is written in a sequence file or a map file as a sequence of bytes.

h3. Splitting Strategy
In the current version of Hadoop (0.20.1) opening a file in append mode is disabled since it's not enough reliable. So, for the moment, it's only possible to create new files. The Camel HDFS endpoint tries to solve this problem in this way:
* If the split strategy option has been defined, the actual file name will become a directory name and a <file name>/seg0 will be initially created.
* Every time a splitting condition is met a new file is created with name <original file name>/segN where N is 1, 2, 3, etc.
The splitStrategy option  is defined as a string with the following syntax:
splitStrategy=<ST>:<value>,<ST>:<value>,*

where <ST> can be:
* BYTES a new file is created, and the old is closed when the number of written bytes is more than <value>
* MESSAGES a new file is created, and the old is closed when the number of written messages is more than  <value>
* IDLE a new file is created, and the old is closed when no writing happened in the last <value> milliseconds

for example:
{code}
hdfs://localhost/tmp/simple-file?splitStrategy=IDLE:1000,BYTES:5
{code}
it means: a new file is created either when it has been idle for more than 1 second or if more than 5 bytes have been written. So, running {{hadoop fs -ls /tmp/simple-file}} you'll find the following files seg0, seg1, seg2, etc