As the Red Hat Summit shifts to the west coast in San Francisco this year Hortonworks and Red Hat will be demonstrating the progress of our engineering efforts. Our engineers have been hard at work in the factories and in the communities deeply integrating our open source offerings to create a comprehensive platform for new analytic applications. As a reminder in February Red Hat and Hortonworks announced a comprehensive open source initiative to deliver infrastructure solutions to bring 100-percent open source Hadoop to the hybrid cloud.…
The Hortonworks Blog
The community fixed 411 JIRAs for 2.4.0 (on top of the 511 JIRAs resolved for 2.3.0). Of the 411 fixes:
- 50 are in Hadoop Common,
- 171 are in HDFS,
- 160 are in YARN and
- 30 went into MapReduce
Hadoop 2.4.0 is the second Hadoop release in 2014, following Hadoop 2.3.0’s February release and its key enhancements to HDFS such as Support for Heterogeneous Storage and In-Memory Cache.…
One of the key concerns in the financial industry today is the alarming increase in fraudulent activities. It is estimated that over $12 billion is spent on fraud detection and prevention and that number is projected to increase significantly over the next few years. Customer data gets compromised and this leads to a decreased level of customer satisfaction and retention, which results in revenue declines for financial organizations.
As financial institutions continue to embrace the adoption of big data infrastructures like the Hortonworks Data Platform based on Hadoop, there is a wealth of information collected that can help with more sophisticated fraud detection. …
Apache Tez is an alternative to MapReduce that provides a powerful framework for executing a complex topology of tasks for data access in Hadoop. Version 0.4 incorporates the feedback from extensive testing of Tez 0.3, released just last month.
This release is especially meaningful because it coincides with completion of the Stinger Initiative (a collaborative community effort involving 145 developers across 44 companies) and the upcoming release of Apache Hive 0.13.…
Securing any system requires you to implement layers of protection. Access Control Lists (ACLs) are typically applied to data to restrict access to data to approved entities. Application of ACLs at every layer of access for data is critical to secure a system. The layers for hadoop are depicted in this diagram and in this post we will cover the lowest level of access… ACLs for HDFS.
This is part of the HDFS Developer Trail series. …
Yesterday our partner Teradata announced a new capability called Teradata QueryGrid that further deepens the integration between the Teradata Data Warehouse and the Hortonworks Data Platform. This announcement is important because it delivers on the promise and the value of the Modern Data Architecture by demonstrating how the two technologies complement each other for the enterprise.
Teradata pioneered deeper integration with Apache Hadoop through integration with H-Catalog initially with Aster SQL-H and then the Data Warehouse and now they have taken it to the next level with Teradata QueryGrid.…
Today we are proud to announce that the formation of a terrific partnership with LucidWorks to bring search to the Hortonworks Data Platform. LucidWorks delivers an enterprise-grade search development platform built atop the power of Apache Solr.Presentation & Applications Enable both existing and new applications to provide value to the organization. Enterprise Management & Security Empower existing operations and security tools to manage Hadoop. Governance Integration Data Workflow, Lifecycle & Governance
If you’re excited to get started with the new features in Hortonworks Data Platform 2.1, then we’ve included 4 tutorials for you try out – Sandbox-style.
You can download the HDP 2.1 Technical Preview here, and then get stuck into these great tutorials.Interactive Query with Apache Hive and Apache Tez
OK, so you’re not going to get huge performance out of a one-node VM, but you can try out Hive on Tez, and see the performance gains versus MapReduce, and also try out features such as Vectorized Query, and the host of new SQL features.…
The pace of innovation within the Apache Hadoop community is truly remarkable, enabling us to announce the availability of Hortonworks Data Platform 2.1, incorporating the very latest innovations from the Hadoop community in an integrated, tested, and completely open enterprise data platform.
There is no doubt that enterprises recognize how Big Data is crucial to monetizing their business. The information contained in the volumes of data collected can offer key insights into product, customer and competitive trends. There are a variety of sophisticated tools for Big Data analytics and processing but most big data implementations are based on rudimentary technologies like FTP based scripts for data collection and distribution.
Although FTP is a widely used protocol, there is an inherent lack of reliability in this approach. …
Apache Falcon is a data governance engine that defines, schedules, and monitors data management policies. Falcon allows Hadoop administrators to centrally define their data pipelines, and then Falcon uses those definitions to auto-generate workflows in Apache Oozie.
InMobi is one of the largest Hadoop users in the world, and their team began the project 2 years ago. At the time, InMobi was processing billions of ad-server events in Hadoop every day.…
We are excited to welcome Blackrock and Passport Capital as Hortonworks investors who today led a $100M round of funding with continued participation from all existing investors.
This latest round of funding will allow us to double-down on our founding strategy: to make open source Apache Hadoop a true enterprise data platform. To that end we are focused in two areas:1. Lead the innovation of Hadoop. In open source, for everyone.…
In February 2014, the Apache Storm community released Storm version 0.9.1. Storm is a distributed, fault-tolerant, and high-performance real-time computation system that provides strong guarantees on the processing of data. Hortonworks is already supporting customers using this important project today.
Many organizations have already used Storm, including our partner Yahoo! This version of Apache Storm (version 0.9.1) is:
- Highly scalable. Like Hadoop, Storm scales linearly
- Fault-tolerant. Automatically reassigns tasks if a node fails
LDAP provides a central source for maintaining users and groups within an enterprise. There are two ways to use LDAP groups within Hadoop. The first is to use OS level configuration to read LDAP groups. The second is to explicitly configure Hadoop to use LDAP-based group mapping.
Here is an overview of steps to configure Hadoop explicitly to use groups stored in LDAP.
- Create Hadoop service accounts in LDAP
- Shutdown HDFS NameNode & YARN ResourceManager
- Modify core-site.xml to point to LDAP for group mapping
- Re-start HDFS NameNode & YARN ResourceManager
- Verify LDAP based group mapping
Prerequisites: Access to LDAP and the connection details are available.…
Hortonworks would like to congratulate Leslie Lamport on winning the 2013 Turing Award given by the Association of Computing Machinery. This award is essentially the equivalent of the Nobel Prize for computer science. Among Lamport’s many and varied contributions to the field computer science are: TLA (Temporal Logic for Actions), LaTeX and PAXOS.