Does MapReduce work with HBase?

1 Answer. Of course you can, HBase comes with a TableMapReduceUtil to help you configuring MapReduce jobs for scanning data. It will automatically create a map task for each region.

What is MapReduce in HBase?

The reduce process builds its results but emits the row key as an ImmutableBytesWritable and a Put command to store the results back to HBase. Finally, the results are stored in HBase by the HBase MapReduce infrastructure. (You do not need to execute the Put commands.)

How do I use MapReduce in cloudera?

Running a MapReduce Job

1. Log into a host in the cluster.
2. Run the Hadoop PiEstimator example using the following command: yarn jar /opt/cloudera/parcels/CDH/lib/hadoop-mapreduce/hadoop-mapreduce-examples.jar pi 10 100.
3. In Cloudera Manager, navigate to Cluster > ClusterName > yarn Applications.
4. Check the results of the job.

What is HBase not good for?

When to use HBase HBase is not optimized for classic transactional applications or even relational analytics. If you find that your data is stored in collections, for example some meta data, message data or binary data that is all keyed on the same value, then you should consider HBase.

What is HDFS HBase?

HDFS is a Java-based file system utilized for storing large data sets. HBase is a Java based Not Only SQL database. HDFS has a rigid architecture that does not allow changes. It doesn’t facilitate dynamic storage. HBase allows for dynamic changes and can be utilized for standalone applications.

What is Immutablebyteswritable?

A byte sequence that is usable as a key or value. Based on BytesWritable only this class is NOT resizable and DOES NOT distinguish between the size of the sequence and the current capacity as BytesWritable does. Hence its comparatively ‘immutable’.

What is HBase good for?

HBase provides a fault-tolerant way of storing sparse data sets, which are common in many big data use cases. It is well suited for real-time data processing or random read/write access to large volumes of data. A sort order can also be defined for the data. HBase relies on ZooKeeper for high-performance coordination.

What is the advantage of HBase?

Advantages of HBase Can store large data sets on top of HDFS file storage and will aggregate and analyze billions of rows present in the HBase tables. In HBase, the database can be shared. Operations such as data reading and processing will take small amount of time as compared to traditional relational models.

Why is MapReduce needed?

MapReduce facilitates concurrent processing by splitting petabytes of data into smaller chunks, and processing them in parallel on Hadoop commodity servers. In the end, it aggregates all the data from multiple servers to return a consolidated output back to the application.