Sqoop: All content tagged as Sqoop in NoSQL databases and polyglot persistence
Thursday, 11 November 2010
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.
HDFS
A distributed file system that provides high throughput access to application data.
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.
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.
HBase
A scalable, distributed database that supports structured data storage for large tables.
Avro
A data serialization system. Similar to ☞ Thrift and ☞ Protocol Buffers.
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
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.
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.
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).
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.
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.
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.
Mahout
A Scalable machine learning and data mining library.
Integration with Relational databases
- Oracle
- Hadoop connector for Oracle Ora-Oop
- Hadoop and Oracle Parallel Processing
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)
Friday, 15 October 2010
Membase and Cloudera with Flume and Sqoop
James Phillips (Membase):
On the technology integration front, we have built and are making available to customers two mechanisms for integrating Membase and Cloudera Distribution for Hadoop (CDH). The first is a Membase NodeCode module that can stream data from Membase to CDH in real-time. As new operational data enters Membase, it can be massaged in real time and pumped into a CDH cluster for processing. The second is a Sqoop-derived batch loader utility that enables loading of data from Membase to CDH, and vice versa.
Real-time integration using Flume. Batch integration using Sqoop. Sounds like Cloudera’s tools are delivering.
Original title and link: Membase and Cloudera with Flume and Sqoop (NoSQL databases © myNoSQL)
via: http://www.infoq.com/news/2010/10/membase-cdh-integration
Thursday, 16 September 2010
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/
Tuesday, 29 June 2010
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.
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