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Oozie: All content tagged as Oozie in NoSQL databases and polyglot persistence

A prolific season for Hadoop and its ecosystem

In 4 years of writing this blog I haven’t seen such a prolific month:

  • Apache Hadoop 2.2.0 (more links here)
  • Apache HBase 0.96 (here and here)
  • Apache Hive 0.12 (more links here)
  • Apache Ambari 1.4.1
  • Apache Pig 0.12
  • Apache Oozie 4.0.0
  • Plus Presto.

Actually I don’t think I’ve ever seen such an ecosystem like the one created around Hadoop.

Original title and link: A prolific season for Hadoop and its ecosystem (NoSQL database©myNoSQL)


Hortonworks Data Platform 1.0

Hortonworks has announced the 1.0 release of the Hortonworks Data Platform prior to the Hadoop Summit 2012 together with a lot of supporting quotes from companies like Attunity, Dataguise, Datameer, Karmasphere, Kognitio, MarkLogic, Microsoft, NetApp, StackIQ, Syncsort, Talend, 10gen, Teradata, and VMware.

Some info points:

  1. Hortonworks Data Platform is a platform meant to simplify the installation, integration, management, and use of Apache Hadoop

    hdp-diagram

    1. HDP 1.0 is based on Apache Hadoop 1.0
    2. Apache Ambari is used for installation and provisioning
    3. The same Apache Amabari is behind the Hortonworks Management Console
    4. For Data integration, HDP offers WebHDFS, HCatalog APIs, and Talend Open Studio
    5. Apache HCatalog is the solution offering metadata and table management
  2. Hortonworks Data Platform is 100% open source—I really appreciate Hortonworks’s dedication to the Apache Hadoop project and open source community

  3. HDP comes with 3 levels of support subscriptions, pricing starting at $12500/year for a 10 nodes cluster

One of the most interesting aspects of the Hortonworks Data Platform release is that the high-availability (HA) option for HDP is based on using VMWare-powered virtual machines for the NameNode and JobTracker. My first thought about this approach is that it was chosen to strengthen a partnership with VMWare. On the other hand, Hadoop 2.0 contains already a new highly-available version of the NameNode (Cloudera Hadoop Distribution uses this solution) and VMWare has bigger plans for a virtualization-friendly Hadoop environment with project Serengeti.

You can read a lot of posts about this announcement, but you’ll find all the details in Hortonworks’s John Kreisa’s post here and the PR announcement.

Original title and link: Hortonworks Data Platform 1.0 (NoSQL database©myNoSQL)


Apache Bigtop: Apache Big Data Management Distribution Based on Apache Hadoop

Apache Bigtop:

The primary goal of Bigtop is to build a community around the packaging and interoperability testing of Hadoop-related projects. This includes testing at various levels (packaging, platform, runtime, upgrade, etc…) developed by a community with a focus on the system as a whole, rather than individual projects.

Currently packaging:

  • Apache Hadoop 1.0.x
  • Apache Zookeeper 3.4.3
  • Apache HBase 0.92.0
  • Apache Hive 0.8.1
  • Apache Pig 0.9.2
  • Apache Mahout 0.6.1
  • Apache Oozie 3.1.3
  • Apache Sqoop 1.4.1
  • Apache Flume 1.0.0
  • Apache Whirr 0.7.0

Apache Bigtop looks like the first step towards the Big Data LAMP-like platform analysts are calling for. Practically though it’s goal is to ensure that all the components of the wide Hadoop ecosystem remain interoperable.

Original title and link: Apache Bigtop: Apache Big Data Management Distribution Based on Apache Hadoop (NoSQL database©myNoSQL)


The components and their functions in the Hadoop ecosystem

Edd Dumbill enumerates the various components of the Hadoop ecosystem:

Hadoop ecosystem

My quick reference of the Hadoop ecosystem is including a couple of other tools that are not in this list, with the exception of Ambari and HCatalog which were released later.

Original title and link: The components and their functions in the Hadoop ecosystem (NoSQL database©myNoSQL)


A Detailed Guide to Oozie

Boris Lublinsky and Michael Segel series of articles about Oozie, the Hadoop workflow framework, published on InfoQ:

  • Introduction to Oozie

    Oozie workflow is a collection of actions (i.e. Hadoop Map/Reduce jobs, Pig jobs) arranged in a control dependency DAG (Direct Acyclic Graph), specifying a sequence of actions execution. This graph is specified in hPDL (a XML Process Definition Language).

  • Oozie by Example

    In this article we will describe a more complex Oozie example, which will allow us to discuss more Oozie features and demonstrate how to use them. The workflow which we are describing here implements vehicle GPS probe data ingestion. Probes data is delivered to a specific HDFS directory hourly in a form of file, containing all probes for this hour. Probes ingestion is done daily for all 24 files for this day. If the amount of files is 24, an ingestion process should start. […]

  • Extending Oozie

    In this article we will show how to leverage Oozie extensibility to implement custom orchestration language extensions.

These should be enough not only to give you on overview of Oozie but also a good start to using it when complex workflows are needed by your Hadoop MapReduce jobs.

Original title and link: A Detailed Guide to Oozie (NoSQL database©myNoSQL)


Biodiversity Indexing: Offline Processing With Hadoop, Hive, Sqoop, Oozie

The architecture for offline processing biodiversity based on Sqoop, Hadoop, Oozie, and Hive:

Hadoop Sqoop Oozie Hive Biodiversity Indexing

And its future:

Following this processing work, we expect to modify our crawling to harvest directly into HBase. The flexibility HBase offers will allow us to grow incrementally the richness of the terms indexed in the Portal, while integrating nicely into Hadoop based workflows. The addition of coprocessors to HBase is of particular interest to further reduce the latency involved in processing, by eliminating batch processing altogether.

Many companies working with large datasets have to deal with multiple systems and duplicate data between the online services and offline processors. While the infrastructure costs are going down, the costs of complexity are not. The HBase + Hadoop and Cassandra + Brisk combos are starting to address this problem.

Original title and link: Biodiversity Indexing: Offline Processing With Hadoop, Hive, Sqoop, Oozie (NoSQL database©myNoSQL)

via: http://www.cloudera.com/blog/2011/06/biodiversity-indexing-migration-from-mysql-to-hadoop/


Experimenting with Hadoop using Cloudera VirtualBox Demo

CDH Mac OS X VirtualBox VM

If you don’t count the download, you’ll get this up and running in 5 minutes tops. At the end you’ll have Hadoop, Sqoop, Pig, Hive, HBase, ZooKeeper, Oozie, Hume, Flume, and Whirr all configured and ready to experiment with.

Making it easy for users to experiment with these tools increases the chances for adoption. Adoption means business.

Original title and link: Experimenting with Hadoop using Cloudera VirtualBox Demo (NoSQL databases © myNoSQL)

via: http://www.cloudera.com/blog/2011/06/cloudera-distribution-including-apache-hadoop-3-demo-vm-installation-on-mac-os-x-using-virtualbox-cdh/


The Backstory of Yahoo and Hadoop

We currently have nearly 100 people working on Apache Hadoop and related projects, such as Pig, ZooKeeper, Hive, Howl, HBase and Oozie. Over the last 5 years, we’ve invested nearly 300 person-years into these projects. […] Today Yahoo runs on over 40,000 Hadoop machines (>300k cores). They are used by over a thousand regular users from our science and development teams. Hadoop is at the center of our research in search, advertising, spam detection, personalization and many other topics.

I assume there’s no surpise to anyone I’m a big fan of Yahoo! open source initiatives.

Original title and link: The Backstory of Yahoo and Hadoop (NoSQL databases © myNoSQL)

via: http://developer.yahoo.com/blogs/hadoop/posts/2011/01/the-backstory-of-yahoo-a


Quick Reference: Hadoop Tools Ecosystem

Just a quick reference of the continuously growing Hadoop tools ecosystem.

Hadoop

The Apache Hadoop project develops open-source software for reliable, scalable, distributed computing.

hadoop.apache.org

HDFS

A distributed file system that provides high throughput access to application data.

hadoop.apache.org/hdfs/

MapReduce

A software framework for distributed processing of large data sets on compute clusters.

Amazon Elastic MapReduce

Amazon Elastic MapReduce is a web service that enables businesses, researchers, data analysts, and developers to easily and cost-effectively process vast amounts of data. It utilizes a hosted Hadoop framework running on the web-scale infrastructure of Amazon Elastic Compute Cloud (Amazon EC2) and Amazon Simple Storage Service (Amazon S3).

aws.amazon.com/elasticmapreduce/

Cloudera Distribution for Hadoop (CDH)

Cloudera’s Distribution for Hadoop (CDH) sets a new standard for Hadoop-based data management platforms.

cloudera.com/hadoop

ZooKeeper

A high-performance coordination service for distributed applications. ZooKeeper is a centralized service for maintaining configuration information, naming, providing distributed synchronization, and providing group services.

hadoop.apache.org/zookeeper/

HBase

A scalable, distributed database that supports structured data storage for large tables.

hbase.apache.org

Avro

A data serialization system. Similar to ☞ Thrift and ☞ Protocol Buffers.

avro.apache.org

Sqoop

Sqoop (“SQL-to-Hadoop”) is a straightforward command-line tool with the following capabilities:

  • Imports individual tables or entire databases to files in HDFS
  • Generates Java classes to allow you to interact with your imported data
  • Provides the ability to import from SQL databases straight into your Hive data warehouse

cloudera.com/downloads/sqoop/

Flume

Flume is a distributed, reliable, and available service for efficiently moving large amounts of data soon after the data is produced.

archive.cloudera.com/cdh/3/flume/

Hive

Hive is a data warehouse infrastructure built on top of Hadoop that provides tools to enable easy data summarization, adhoc querying and analysis of large datasets data stored in Hadoop files. It provides a mechanism to put structure on this data and it also provides a simple query language called Hive QL which is based on SQL and which enables users familiar with SQL to query this data. At the same time, this language also allows traditional map/reduce programmers to be able to plug in their custom mappers and reducers to do more sophisticated analysis which may not be supported by the built-in capabilities of the language.

hive.apache.org

Pig

A high-level data-flow language and execution framework for parallel computation. Apache Pig is a platform for analyzing large data sets that consists of a high-level language for expressing data analysis programs, coupled with infrastructure for evaluating these programs. The salient property of Pig programs is that their structure is amenable to substantial parallelization, which in turns enables them to handle very large data sets.

pig.apache.org

Oozie

Oozie is a workflow/coordination service to manage data processing jobs for Apache Hadoop. It is an extensible, scalable and data-aware service to orchestrate dependencies between jobs running on Hadoop (including HDFS, Pig and MapReduce).

yahoo.github.com/oozie

Cascading

Cascading is a Query API and Query Planner used for defining and executing complex, scale-free, and fault tolerant data processing workflows on a Hadoop cluster.

cascading.org

Cascalog

Cascalog is a tool for processing data on Hadoop with Clojure in a concise and expressive manner. Cascalog combines two cutting edge technologies in Clojure and Hadoop and resurrects an old one in Datalog. Cascalog is high performance, flexible, and robust.

github.com/nathanmarz/cascalog

HUE

Hue is a graphical user interface to operate and develop applications for Hadoop. Hue applications are collected into a desktop-style environment and delivered as a Web application, requiring no additional installation for individual users.

archive.cloudera.com/cdh3/hue

You can read more about HUE on ☞ Cloudera blog.

Chukwa

Chukwa is a data collection system for monitoring large distributed systems. Chukwa is built on top of the Hadoop Distributed File System (HDFS) and Map/Reduce framework and inherits Hadoop’s scalability and robustness. Chukwa also includes a flexible and powerful toolkit for displaying, monitoring and analyzing results to make the best use of the collected data.

incubator.apache.org/chukwa/

Mahout

A Scalable machine learning and data mining library.

mahout.apache.org

Integration with Relational databases

Integration with Data Warehouses

The only list I have is MapReduce, RDBMS, and Data Warehouse, but I’m afraid it is quite a bit old. So maybe someone could help me update it.

Anything else? Once we validate this list, I’ll probably have to move it on the NoSQL reference

Original title and link: Quick Reference: Hadoop Tools Ecosystem (NoSQL databases © myNoSQL)


Cloudera: All Your Big Data Are Belong to Us

Matt Asay (GigaOm):

Where Cloudera shines, however, is in taking these different contributions and making Hadoop relevant for enterprise IT[8], where data mining has waxed and waned over the years. […] Cloudera, in other words, is banking on the complexity of Hadoop to drive enterprise IT to its own Cloudera Enteprise tools.

Additionally, I think what Cloudera is “selling” is a good set of tools — Hadoop, HBase, Hive, Pig, Oozie, Sqoop, Flume, Zookeeper, Hue — put together based on their expertise in the field.

Original title and link: Cloudera: All Your Big Data Are Belong to Us (NoSQL databases © myNoSQL)

via: http://cloud.gigaom.com/2010/09/14/cloudera-all-your-big-data-are-belong-to-us/


5 Years Old Hadoop Celebration at Hadoop Summit, Plus New Tools

I didn’t realize Hadoop has been so long on the market: 5 years. In just a couple of hours, the celebration will start at ☞ Hadoop Summit in Santa Clara.

Yahoo!, the most active contributor to Hadoop, will ☞ open source today two new tools: Hadoop with Security and Oozie, a workflow engine.

Hadoop Security integrates Hadoop with Kerberos, providing secure access and processing of business-sensitive data.This enables organizations to leverage and extract value from their data and hardware investment in Hadoop across the enterprise while maintaining data security, allowing new collaborations and applications with business-critical data.

Oozie is an open-source workflow solution to manage jobs running on Hadoop, including HDFS, Pig, and MapReduce. Oozie — a name for an elephant tamer — was designed for Yahoo!’s rigorous use case of managing complex workflows and data pipelines at global scale. It is integrated with Hadoop Security and is quickly becoming the de-facto standard for ETL (extraction, transformation, loading) processing at Yahoo!.

Update: It looks like the news are not stopping here, Cloudera making ☞ a big announcement accompanying the new release of Cloudera’s Distribution for Hadoop CDHv3 Beta2:

The additional packages include HBase, the popular distributed columnar storage system with fast read-write access to data managed by HDFS, Hive and Pig for query access to data stored in a Hadoop cluster, Apache Zookeeper for distributed process coordination and Sqoop for moving data between Hadoop and relational database systems. We’ve adopted the outstanding workflow engine out of Yahoo!, Oozie, and have made contributions of our own to adapt it for widespread use by general enterprise customers. We’ve also released – this is a big deal, and I’m really pleased to announce it – our continuous data loading system, Flume, and our Hadoop User Environment software (formerly Cloudera Desktop, and henceforth “Hue”) under the Apache Software License, version 2.

Also worth mentioning, going forward Cloudera will also have a commercial offering: ☞ Cloudera Enterprise:

Cloudera Enterprise combines the open source CDHv3 platform with critical monitoring, management and administrative tools that our enterprise customers have told us they need to put Hadoop into production. We’ve added dashboards for critical IT tasks, including monitoring cluster status and activity, keeping track of data flows into Hadoop in real time based on the services that Flume provides, and controlling access to data and resources by users and groups. We’ve integrated access controls with Active Directory and other LDAP implementations so that IT staff can control rights and identities in the same way as they do for other business platforms they use. Cloudera Enterprise is available by annual subscription and includes maintenance, updates and support.