From the Dev Team

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This three part series is co-authored by Ofer Mendelevitch, director of data science at Hortonworks, and Jiwon Seo, Ph.D. and research assistant at Stanford University.

Introduction

This is the third part of the blog-post series about anomaly detection from healthcare data.

In part 1, we described the dataset, the business use-case and our general approach of applying graph algorithms (specifically the personalized-PageRank algorithm) to detect anomalies in the Medicare-B dataset.…

Apache Ambari is the only 100% open source management and provisioning tool for Apache Hadoop. Recent innovations of Apache Ambari have focused on opening Apache Ambari into a pluggable management platform that can automate cluster provisioning, deploy 3rd party software and provide custom operational and developers’ views to the end user.

Join us Thursday March 26 at 10am PT, for an online technical workshop where we will cover 3 key integration points of Apache Ambari including Stacks, Views and Blueprints and deliver working examples of each.…

We hosted an Apache Slider Meetup at our Hortonworks Santa Clara office on March 4th, where committers, contributors, and community members interested in the Apache Slider congregated to hear what’s happening.

There were two presenters. To set the context for the audience, Steve Loughran, member of technical staff at Hortonworks, delivered an extemporaneous high-level overview of Apache Slider within Apache Hadoop YARN framework.

Running Dockerized Applications on YARN via Slider

Yu “Thomas” Liu gave a demo of his hot-off-the-IDE docker deployment work.…

Introduction

Today, organizations use the Apache Hadoop™ stack in the form of a central data lake to store their critical datasets and power their analytical processing workloads. A key requirement for the Hadoop cluster and the services running on it is to be highly available and flawlessly continue to function while software is being upgraded. In the past, the Hadoop community has added enterprise features such as High Availability (HA) to various components of the stack, snapshots, improved disaster recovery etc.…

This three part series is co-authored by Ofer Mendelevitch, director of data science at Hortonworks, and Jiwon Seo, Ph.D. and research assistant at Stanford University.

Introduction

This is the second part of our blog-post series about anomaly detection from healthcare data. As described in part 1, our goal is to apply the personalized-PageRank algorithm to detect anomaly in healthcare payment records, specifically the publicly available Medicare-B dataset.

In this blog post, we demonstrate the technical steps to compute the similarity graph between medical providers at scale, using HDP and Apache Pig.…

Apache Hive is the de facto standard for SQL in Hadoop with more enterprises relying on this open source project than any other alternative. Stinger.next, a community based effort, is delivering true enterprise SQL at Hadoop scale and speed.

With Hive’s prominence in the enterprise, security within Hive has come under greater focus from enterprise users. They have come to expect fine grain access control and auditing within Hive. Apache Ranger provides centralized security administration for Hadoop, and it enables fine grain access control and deep auditing for Apache components such as Hive, HBase, HDFS, Storm and Knox.…

HDP 2.2 brings substantial innovations in Apache Hadoop YARN, enabling users of Apache Hadoop to efficiently store their data in a single repository and interact with it simultaneously using a wide variety of engines. This functionality makes YARN particularly attractive for the integration of many distributed Long-Running services.

In this release, we also introduced a new framework Apache™ Slider for easy on boarding of Long-Running service on top of YARN.…

This three part series is co-authored by Ofer Mendelevitch, director of data science at Hortonworks, and Jiwon Seo, Ph.D. and research assistant at Stanford University.

Introduction

PageRank[1]is the poster-child of graph algorithms, used by Google in its original search engine system to determine which web pages are most influential. The incredible success of PageRank led do increased interest and research in the field of graph algorithms, resulting in innovative extensions such as personalized PageRank [2].…

This is the second post in a series exploring the theme of long-running service workloads in YARN. See for the introductory post.

Long-running services deployed on YARN are by definition expected to run for a long period of time—in many cases forever. Services such as Apache™ HBase, Apache Accumulo and Apache Storm can be run on YARN to provide a layer of services to end users, and they usually have a central master running in conjunction with an ApplicationMaster (AM).…

Analysts and data scientists⎯not to mention business executives⎯want Big Data not for the sake of the data itself, but for the ability to work with and learn from that data. As other users become more savvy, they also want more access. But too many inefficient queries can create a bottleneck in the system.

The good news is that Apache™ Hive 0.14—the standard SQL interface for processing, accessing and analyzing Apache Hadoop® data sets—is now powered by Apache Calcite.…

This is the third post in a series exploring recent innovations in the Hadoop ecosystem that are included in Hortonworks Data Platform (HDP) 2.2. In this post, we introduce the theme of supporting rolling upgrades and downgrades of a Hadoop YARN cluster.

HDP 2.2 offers substantial innovations in Apache™ Hadoop YARN, enabling Hadoop users to efficiently store and interact with their data in a single repository, simultaneously using a wide variety of engines.…

As a data scientist working with Hadoop, I often use Apache Hive to explore data, make ad-hoc queries or build data pipelines.

Until recently, optimizing Hive queries focused mostly on data layout techniques such as partitioning and bucketing or using custom file formats.

In the last couple of years, driven largely by the innovation of the Hive community around the Stinger initiative, Hive query time has improved dramatically, enabling Hive to support both batch and interactive workloads at speed and at scale.…

The Apache HBase community has released Apache HBase 1.0.0. Seven years in the making, it marks a major milestone in the Apache HBase project’s development, offers some exciting features and new API’s without sacrificing stability, and is both on-wire and on-disk compatible with HBase 0.98.x.

In this blog, which is a cross post from from Apache HBase Blog, we look at the past, present and future of Apache HBase project.…

Hortonworks Data Platform’s YARN-based architecture enables multiple applications to share a common cluster and data set while ensuring consistent levels of response made possible by a centralized architecture. Hortonworks led the efforts to on-board open source data processing engines, such as Apache Hive, HBase, Accumulo, Spark, Storm and others, on Apache Hadoop YARN.

In this blog, we will focus on one of those data processing engines—Apache Storm—and its relationship with Apache Kafka.…

Since our founding in 2011, Hortonworks has had a fundamental belief: the only way to deliver infrastructure platform technology is completely in open source. Moreover, we believe that collaborative open source software development under the governance model of an entity like the Apache Software Foundation (ASF) is the best way to accelerate innovation that targets enterprise end users since it brings the largest number of developers together in a way that enables innovation to happen far faster than any single vendor could achieve and in a way that is free of friction for the enterprise.…