HDFS now includes (shipping in CDH 5.8.2 and later) a comprehensive storage capacity-management approach for moving data across nodes.
In HDFS, the DataNode spreads the data blocks into local filesystem directories, which can be specified using dfs.datanode.data.dir in hdfs-site.xml. In a typical installation, each directory, called a volume in HDFS terminology, is on a different device (for example, on separate HDD and SSD).
When writing new blocks to HDFS,
Today, Cloudera announced the availability of an Apache Spark 2.0 Beta release for users of the Cloudera platform.
Apache Spark 2.0 is tremendously exciting (read this post for more background) because (among other things):
- The Dataset API further enhances Spark’s claim as the best tool for data engineering by providing compile-time type safety along with the benefits of a query-optimization engine.
- The Structured Streaming API enables the modeling of streaming data as a continuous DataFrame and expresses operations on that data with a SQL-like API.
Last week, the open source Open Network Insights (ONI) project, now called Spot, was accepted into the ASF Incubator. Here are the highlights about its open data model approach and initial use cases.
One of the biggest challenges organizations face today in combating cyber threats is collecting and normalizing data from numerous security event data sources (often up to thousands of them) to build the required analytics.
The Apache Hadoop project recently announced its 3.0.0-alpha1 release.
Given the scope of a new major release, the Apache Hadoop community decided to release a series of alpha and beta releases leading up to 3.0.0 GA. This gives downstream applications and end users an opportunity to test and provide feedback on the changes, which can be incorporated during the alpha and beta process.
The 3.0.0-alpha1 release incorporates thousands of new fixes,
In this guest post, Skool’s architects at BT Group explain its origins, design, and functionality.
With increased adoption of big data comes the challenge of integrating existing data sitting in various relational and file-based systems with Apache Hadoop infrastructure. Although open source connectors (such as Apache Sqoop) and utilities (such as Httpfs/Curl on Linux) make it easy to exchange data, data engineering teams often spend an inordinate amount of time writing code for this purpose.