From the Dev Team

Follow the latest developments from our technical team

On December 4th, Hortonworks presented the fifth of 8 Discover HDP 2.2 webinars: Apache Kafka and Apache Storm for Stream Data Processing. Taylor Goetz, Rajiv Onat, and Justin Sears hosted this 5th webinar in the series.

After Justin Sears set the stage for the webinar by explaining the drivers behind Modern Data Architecture (MDA), Rajiv Onat and Taylor Goetz introduced and discussed how to use Apache Kafka and Apache Storm for stream data processing.…

With Apache Hadoop YARN as its architectural center, Apache Hadoop continues to attract new engines to run within the data platform, as organizations want to efficiently store their data in a single repository and interact with it for batch, interactive and real-time streaming use cases. Apache Storm brings real-time data processing capabilities to help capture new business opportunities by powering low-latency dashboards, security alerts, and operational enhancements integrated with other applications running in the Hadoop cluster.…

Hortonworks architects vertically integrate the projects within our Hadoop distribution with YARN and HDFS in order to enable HDP to span workloads from batch, interactive, and real time—across both open source and other data access technologies. In HDP 2.2, we deliver work to vertically integrate Apache Storm, Apache Accumulo and Apache HBase so that all of those long-running services run in Hadoop on YARN via Apache Slider.

The Apache Slider community recently released Apache Slider 0.60.0.…

On November 13th, Hortonworks presented the fourth of 8 Discover HDP 2.2 webinars: Rohit Bakhshi, Jitendra Pandey, and Justin Sears hosted this 4th webinar in the series.

Rohit Bakhshi and Jitendra Pandey introduced HDP and discussed how to use HDFS for reliable, scalable, cost-efficient, and fault tolerant as a distributed data storage platform for your Modern Data Architecture (MDA). They also covered new HDFS data storage innovations now included in HDP 2.2:

  • Heterogeneous storage
  • Encryption
  • Operational security enhancements

Here is the complete recording of the Webinar.…

The Stinger.next initiative, with its focus on transactions, sub-second queries and SQL:2011 Analytics evolves Apache Hive to allow it to run most of the analytical workloads that are typical within a data warehouse, but now at petabyte scale. The first phase of Stinger.Next, delivered in Apache Hive 0.14 and in HDP 2.2, delivers transactions with ACID semantics a critical step in the evolution of the Hive as the defacto standard for SQL in Hadoop.…

With Apache Hadoop YARN as its architectural center, Apache Hadoop continues to attract new engines to run within the data platform, as organizations want to efficiently store their data in a single repository and interact with it in different ways. As YARN propels Hadoop’s emergence as a business-critical data platform, the enterprise requires more stringent data security capabilities. Apache Ranger provides many of these, with central security policy administration across authorization, accounting and data protection.…

The architecture of Hortonworks Data Platform (HDP) matches the blueprint for Enterprise Apache Hadoop, with data management, data access, governance, operations and security. This post focuses on one of those core components: security. Specifically, we will focus on Apache Knox Gateway for securing access to the Hadoop REST APIs.

Pseudo Federation Provider

This blog will walk through the process of adding a new provider for establishing the identity of a user.…

With Apache Hadoop YARN as its architectural center, Apache Hadoop continues to attract new engines to run within the data platform, as organizations want to efficiently store their data in a single repository and interact with it for batch, interactive and real-time streaming use cases. More and more independent software vendors (ISVs) are developing applications to run in Hadoop via YARN. This increases the number of users and processing engines that operate simultaneously across a Hadoop cluster, on the same data, at the same time.…

Introduction

In this 2nd part of the blog post and its accompanying IPython Notebook in our series on Data Science and Apache Hadoop, we continue to demonstrate how to build a predictive model with Apache Hadoop, using existing modeling tools. And this time we’ll use Apache Spark and ML-Lib.

Apache Spark is a relatively new entrant to the Hadoop ecosystem. Now running natively on Apache Hadoop YARN, the architectural center of Hadoop, Apache Spark is an in-memory data processing API and execution engine that is effective for machine learning and data science use cases.…

Hadoop Operations for provisioning, managing and monitoring a cluster are critical to the success of a Hadoop project and having an intuitive and effective set of tooling has become a foundational element of a Hadoop distribution. Within HDP, we provide completely open source Apache Ambari to help you be successful with Hadoop operations.

The rate of innovation in the Ambari community is astonishing and this pace continues with the 7th release of the project this year alone, Apache Ambari 1.7.0.…

Our customers have many choices of infrastructure to deploy HDP: on premise, cloud, virtualized and even as an appliance. Further, our customers have a choice of deploying on Linux and Windows operating systems. You can easily see this creates a complex matrix. At Hortonworks, we believe you should not be limited to just one option but have the option to choose the best combination of infrastructure and operating system based on the usage scenario.…

It gives me great pleasure to announce that the Apache Hadoop community has released Apache Hadoop 2.6.0 !

In particular, we are excited about three major pieces in this release: heterogeneous storage in HDFS with SSD & Memory tiers, support for long-running services in YARN and rolling upgrades—the ability to upgrade your cluster software and restart upgraded nodes without taking the cluster down or losing work in progress. With YARN as its architectural center, Hadoop continues to attract new engines to run within the data platform, as organizations want to efficiently store their data in a single repository and interact with it simultaneously in different ways.…

With YARN as its architectural center, Apache Hadoop continues to attract new engines to run within the data platform, as organizations want to efficiently store their data in a single repository and interact with it simultaneously in different ways. Apache Tez supports YARN-based, high performance batch and interactive data processing applications in Hadoop that need to handle datasets scaling to terabytes or petabytes.

The Apache community just released Apache Pig 0.14.0,and the main feature is Pig on Tez.…

While YARN has allowed new engines to emerge for Hadoop, the most popular integration point with Hadoop continues to be SQL and Apache Hive is still the defacto standard. Although many SQL engines for Hadoop have emerged, their differentiation is being rendered obsolete as the open source community surrounds and advances this key engine at an accelerated rate.

Last week, the Apache Hive community released Apache Hive 0.14, which includes the results of the first phase in the Stinger.next initiative and takes Hive beyond its read-only roots and extends it with ACID transactions.…

A Cosmopolitan Metropolis

Brussels, Belgium, conjures images of a cosmopolitan metropolis, where geopolitical summits are held, where world economic forums are debated, where global European institutions are headquartered, and where citizens and diplomats fluently converse in more than three languages—English, French, Dutch or German, along with other non-official local flavors.

To this colorful collage, add the image of a Hadoop Summit Europe 2015 for big data developers, practitioners, industry experts, and entrepreneurs, who make a difference in the digital world, who fluently code in multiple programming languages—Java, Python, Scala, C++, Pig, SQL, or R—and innovate and incubate Apache projects.…