The Hortonworks Blog

 

In Derrick Harris’ article on GigaOM entitled “EMC to Hadoop competition: See ya, wouldn’t wanna be ya.”, EMC unveiled their new Pivotal HD offering which effectively re-architects the Greenplum analytic database so it sits on top of the Hadoop Distributed File System (HDFS). Scott Yara, Greenplum cofounder, is excited about the new product. Since a key focus for us at Hortonworks is to deeply integrate Hadoop with other data systems (a la our efforts with Teradata, Microsoft, MarkLogic, and others), I’m always excited to see data system providers like Greenplum decide to store their data natively in HDFS.…

Apache Pig version 0.11 was released last week. An Apache Pig blog post summarized the release. New features include:

  • A DateTime datatype, documentation here.
  • A RANK function, documentation here.
  • A CUBE operator, documentation here.
  • Groovy UDFs, documentation here.

And many improvements. Oink it up for Pig 0.11! Hortonworks’ Daniel Dai gave a talk on Pig 0.11 at Strata NY, check it out:…

Last week, the HBase community released 0.94.5, which is the most stable release of HBase so far. The release includes 76 jira issues resolved, with 61 bug fixes, 8 improvements, and 2 new features.

Most of the bug fixes went against the REST server, replication, region assignment, secure client, flaky unit tests, 0.92 compatibility and various stability improvements. Some of the interesting patches in this release are:
[HBASE-3996] – Support multiple tables and scanners as input to the mapper in map/reduce jobs
[HBASE-5416] – Improve performance of scans with some kind of filters.…

We are now less than a month away from the kickoff of Hadoop Summit Europe, taking place March 20-21 in Amsterdam. The excitement from the community is really starting to grow and pass sales are far ahead of where we expected. Much of the buzz is tied directly to the content that will be presented during the conference.

In all, there were be 42 breakout sessions with presenters from more than 20 companies, including representatives from Adobe, eBay, Facebook, HSBC, LinkedIn, Twitter and Yahoo!.…

YARN is part of the next generation Hadoop cluster compute environment. It creates a generic and flexible resource management framework to administer the compute resources in a Hadoop cluster. The YARN application framework allows multiple applications to negotiate resources for themselves and perform their application specific computations on a shared cluster. Thus, resource allocation lies at the heart of YARN.

YARN ultimately opens up Hadoop to additional compute frameworks, like Tez, so that an application can optimize compute for their specific requirements.…

 

Last week, we outlined our approach for delivering an enterprise viable Apache Hadoop distribution in the open.  Simply put: we believe the fastest way to innovate is to do our work within the open source community, introduce enterprise feature requirements into that public domain, and to work diligently to progress existing open source projects and incubate new projects to meet those needs.

In support of our approach, this week we’ve announced the submission of two new incubation projects to the Apache Software foundation together with the launch of the “Stinger Initiative”, all aimed at enhancing the security and performance of Hadoop applications.  …

 

MapReduce has served us well.  For years it has been THE processing engine for Hadoop and has been the backbone upon which a huge amount of value has been created.  While it is here to stay, new paradigms are also needed in order to enable Hadoop to serve an even greater number of usage patterns.  A key and emerging example is the need for interactive query, which today is challenged by the batch-oriented nature of MapReduce. …

 

UPDATE: Since this article was posted, the Stinger initiative has continued to drive to the goal of 100x Faster Hive. You can read the latest information at http://hortonworks.com/stinger

Introduced by Facebook in 2007, Apache Hive and its HiveQL interface has become the de facto SQL interface for Hadoop.  Today, companies of all types and sizes use Hive to access Hadoop data in a familiar way and to extend value to their organization or customers either directly or though a broad ecosystem of existing BI tools that rely on this key proven interface. …

 

Back in the day, in order to secure a Hadoop cluster all you needed was a firewall that restricted network access to only authorized users. This eventually evolved into a more robust security layer in Hadoop… a layer that could augment firewall access with strong authentication. Enter Kerberos.  Around 2008, Owen O’Malley and a team of committers led this first foray into security and today, Kerberos is still the primary way to secure a Hadoop cluster.…

 

As the Release Manager for hadoop-2.x, I’m very pleased to announce the next major milestone for the Apache Hadoop community, the release of hadoop-2.0.3-alpha!

2.0 Enhancements in this Alpha Release

This release delivers significant major enhancements and stability over previous releases in hadoop-2.x series. Notably, it includes:

  • QJM for HDFS HA for NameNode (HDFS-3077) and related stability fixes to HDFS HA
  • Multi-resource scheduling (CPU and memory) for YARN (YARN-2, YARN-3 & friends)
  • YARN ResourceManager Restart (YARN-230)
  • Significant stability at scale for YARN (over 30,000 nodes and 14 million applications so far, at time of release – see more details from folks at Yahoo! 

Pig can easily stuff Redis full of data. To do so, we’ll need to convert our data to JSON. We’ve previously talked about pig-to-json in JSONize anything in Pig with ToJson. Once we convert our data to json, we can use the pig-redis project to load redis.

Build the pig to json project:

git clone git@github.com:rjurney/pig-to-json.git
ant

Then run our Pig code:

/* Load Avro jars and define shortcut */
register /me/Software/pig/build/ivy/lib/Pig/avro-1.5.3.jar
register /me/Software/pig/build/ivy/lib/Pig/json-simple-1.1.jar
register /me/Software/pig/contrib/piggybank/java/piggybank.jar
define AvroStorage org.apache.pig.piggybank.storage.avro.AvroStorage();

register /me/Software/pig-to-json/dist/lib/pig-to-json.jar
register /me/Software/pig-redis/dist/pig-redis.jar

– Enron emails are available at https://s3.amazonaws.com/rjurney_public_web/hadoop/enron.avro
emails = load ‘/me/Data/enron.avro’ using AvroStorage();

json_test = foreach emails generate message_id, com.hortonworks.pig.udf.ToJson(tos) as bag_json;

store json_test into ‘dummy-name’ using com.hackdiary.pig.RedisStorer(‘kv’, ‘localhost’);

Now run our Flask web server:

python server.py

Code for this post is available here: https://github.com/rjurney/enron-pig-tojson-redis-node.…

 

At Hortonworks, our strategy is founded on the unwavering belief in the power of community driven open source software. In the spirit of openness, we think it’s important to share our perspectives around the broader context of how Apache Hadoop and Hortonworks came to be, what we are doing now, and why we believe our unique focus is good for Apache Hadoop, the ecosystem of Hadoop users, and for Hortonworks as well.…

Hadoop Summit Europe 2013, the European extension of the original and world’s largest Apache Hadoop community conference, today announced its official program, featuring a keynote address from 451 Group Analyst and Research Manager for Data Management and Analytics Matt Aslett and 40 use cases and educational sessions from leading industry and community experts. In addition, Hadoop Summit Europe 2013 boasts an impressive list of Platinum, Gold and Silver sponsors, demonstrating ecosystem support for Apache Hadoop from leading producers of software and services for the enterprise.…

According to the Transaction Processing Council, TPC-H is:

The TPC Benchmark™H (TPC-H) is a decision support benchmark. It consists of a suite of business oriented ad-hoc queries and concurrent data modifications. The queries and the data populating the database have been chosen to have broad industry-wide relevance. This benchmark illustrates decision support systems that examine large volumes of data, execute queries with a high degree of complexity, and give answers to critical business questions.…

Please join Hortonworks, Impetus and Entravision/Luminar for a webinar on how big data analytics is being used in the advertising industry to identify predictability models of consumer behavior. The webinar will take place on Tuesday, February 12th at 1pm (EST), 10am (PST).

Register Now

Big data analytics is becoming increasingly useful to professionals in digital media, gaming, healthcare, security, finance and government, and nearly every industry you can name. Companies are analyzing vast amounts of data from various sources to shed light on customer behaviors, accelerate lead conversion, pinpoint security threats and enrich social media marketing efforts.…

Go to page:« First...10...2021222324...30...Last »

Thank you for subscribing!