Comments on: Known applications of MapReduce http://www.dbms2.com/2008/08/26/known-applications-of-mapreduce/ Choices in data management and analysis Thu, 09 Feb 2012 09:22:14 +0000 hourly 1 http://wordpress.org/?v=3.0.3 By: MapReduce replacing complex SQL queries - Enterprise IT Consultant Views on Technologies and Trends http://www.dbms2.com/2008/08/26/known-applications-of-mapreduce/#comment-187007 MapReduce replacing complex SQL queries - Enterprise IT Consultant Views on Technologies and Trends Mon, 11 Oct 2010 06:54:39 +0000 http://www.dbms2.com/?p=500#comment-187007 [...] Google points out that MapReduce is a powerful tool that can be applied for a variety of purposes including distributed grep, distributed sort, web link-graph reversal, term-vector per host, web access log stats, inverted index construction, document clustering, machine learning and statistical machine translation. A much longer list of MapReduce applications is available at http://www.dbms2.com/2008/08/26/known-applications-of-mapreduce/. [...] [...] Google points out that MapReduce is a powerful tool that can be applied for a variety of purposes including distributed grep, distributed sort, web link-graph reversal, term-vector per host, web access log stats, inverted index construction, document clustering, machine learning and statistical machine translation. A much longer list of MapReduce applications is available at http://www.dbms2.com/2008/08/26/known-applications-of-mapreduce/. [...]

]]> By: Introduction to Datameer | DBMS2 -- DataBase Management System Services http://www.dbms2.com/2008/08/26/known-applications-of-mapreduce/#comment-165742 Introduction to Datameer | DBMS2 -- DataBase Management System Services Sat, 17 Apr 2010 03:50:46 +0000 http://www.dbms2.com/?p=500#comment-165742 [...] Datameer seems to be designed for the classic MapReduce use cases of ETL and heavy data [...] [...] Datameer seems to be designed for the classic MapReduce use cases of ETL and heavy data [...]

]]> By: Confluence: Philip Zeyliger http://www.dbms2.com/2008/08/26/known-applications-of-mapreduce/#comment-118625 Confluence: Philip Zeyliger Sun, 26 Apr 2009 21:49:03 +0000 http://www.dbms2.com/?p=500#comment-118625 <strong>Hadoop-MR Use Cases...</strong> I'm trying to college known uses of Hadoop/GFS/MapReduce, and categorize them somewhat.  When possible, citations are great....... Hadoop-MR Use Cases…

I’m trying to college known uses of Hadoop/GFS/MapReduce, and categorize them somewhat.  When possible, citations are great…….

]]> By: Winning with Data: Aster Data Systems Blog » Blog Archive » The Importance of Visibility Across Rows http://www.dbms2.com/2008/08/26/known-applications-of-mapreduce/#comment-117956 Winning with Data: Aster Data Systems Blog » Blog Archive » The Importance of Visibility Across Rows Wed, 22 Apr 2009 18:49:09 +0000 http://www.dbms2.com/?p=500#comment-117956 [...] Examples abound. Consider a SQL/MR function which applies a complex model to score the data in the database, whether it’s scoring a customer for insurance risk, scoring an internet user for an ad’s effectiveness, or scoring a snippet of text for its sentiment. These functions often construct a data structure in memory to accelerate scoring, which works very well with the SQL/MR API: build the data structure once and reuse it across a large number of rows. [...] [...] Examples abound. Consider a SQL/MR function which applies a complex model to score the data in the database, whether it’s scoring a customer for insurance risk, scoring an internet user for an ad’s effectiveness, or scoring a snippet of text for its sentiment. These functions often construct a data structure in memory to accelerate scoring, which works very well with the SQL/MR API: build the data structure once and reuse it across a large number of rows. [...]

]]> By: Infology.Ru » Blog Archive » Несколько тезисов о MapReduce http://www.dbms2.com/2008/08/26/known-applications-of-mapreduce/#comment-101097 Infology.Ru » Blog Archive » Несколько тезисов о MapReduce Mon, 03 Nov 2008 18:31:24 +0000 http://www.dbms2.com/?p=500#comment-101097 [...] Три основных области применения MapReduce [...] [...] Три основных области применения MapReduce [...]

]]> By: Infology.Ru » Blog Archive » Три подхода к распараллеливанию процесса преобразования данных http://www.dbms2.com/2008/08/26/known-applications-of-mapreduce/#comment-98926 Infology.Ru » Blog Archive » Три подхода к распараллеливанию процесса преобразования данных Thu, 09 Oct 2008 20:36:37 +0000 http://www.dbms2.com/?p=500#comment-98926 [...] «Темой Недели»: MapReduce. Когда я опубликовал список канонических приложений MapReduce, мои друзья из компании Aster Data предложили мне еще одно [...] [...] «Темой Недели»: MapReduce. Когда я опубликовал список канонических приложений MapReduce, мои друзья из компании Aster Data предложили мне еще одно [...]

]]> By: Infology.Ru » Blog Archive » Почему MapReduce так важен для хранилищ данных? http://www.dbms2.com/2008/08/26/known-applications-of-mapreduce/#comment-98539 Infology.Ru » Blog Archive » Почему MapReduce так важен для хранилищ данных? Sun, 05 Oct 2008 06:59:11 +0000 http://www.dbms2.com/?p=500#comment-98539 [...] По существу, вы можете сделать все, что угодно с одной записью* - это шаг map. Но вы сильно ограничены в том, как вы можете объединить информацию о многих (часто промежуточных) записях – это шаг reduce. Тем не менее, шаг reduce позволяет вам выполнять подсчет, суммирование и другие операции агрегирования. Сей факт, вкупе с универсальной мощью шагов map, делает MapReduce полезным, по меньшей мере, для трех важных классов приложений: [...] [...] По существу, вы можете сделать все, что угодно с одной записью* – это шаг map. Но вы сильно ограничены в том, как вы можете объединить информацию о многих (часто промежуточных) записях – это шаг reduce. Тем не менее, шаг reduce позволяет вам выполнять подсчет, суммирование и другие операции агрегирования. Сей факт, вкупе с универсальной мощью шагов map, делает MapReduce полезным, по меньшей мере, для трех важных классов приложений: [...]

]]> By: Winning with Data: Aster Data Systems Blog » Blog Archive » MapReduce Educational Resources http://www.dbms2.com/2008/08/26/known-applications-of-mapreduce/#comment-97253 Winning with Data: Aster Data Systems Blog » Blog Archive » MapReduce Educational Resources Wed, 10 Sep 2008 15:45:30 +0000 http://www.dbms2.com/?p=500#comment-97253 [...] If you are unable to attend, or eager to understand, here are some MapReduce resources you may find informative: Aster’s whitepaper on In-Database MapReduce; Google Labs’ MapReduce research paper; Curt Monash’s post on Known Applications of MapReduce. [...] [...] If you are unable to attend, or eager to understand, here are some MapReduce resources you may find informative: Aster’s whitepaper on In-Database MapReduce; Google Labs’ MapReduce research paper; Curt Monash’s post on Known Applications of MapReduce. [...]

]]> By: MapReduce sound bites | DBMS2 -- DataBase Management System Services http://www.dbms2.com/2008/08/26/known-applications-of-mapreduce/#comment-95948 MapReduce sound bites | DBMS2 -- DataBase Management System Services Thu, 28 Aug 2008 18:47:19 +0000 http://www.dbms2.com/?p=500#comment-95948 [...] Three major applications of MapReduce [...] [...] Three major applications of MapReduce [...]

]]> By: Luke Lonergan http://www.dbms2.com/2008/08/26/known-applications-of-mapreduce/#comment-95945 Luke Lonergan Thu, 28 Aug 2008 17:13:59 +0000 http://www.dbms2.com/?p=500#comment-95945 There is a coding tutorial available at this link in the middle of the page: http://www.greenplum.com/resources/mapreduce/ Key things to note about Greenplum's MR implementation: - It's very similar in form and expression to Google and Hadoop - Extensions for Joins and Pipelined task execution - Native parallel file access - Parallelism is full and transparent to the programmer In summary: we have implemented MapReduce within which you can write SQL, Perl, Python and many more languages. It is straightforward to use MR programs written for Hadoop or Google and port them to Greenplum. There is a coding tutorial available at this link in the middle of the page: http://www.greenplum.com/resources/mapreduce/

Key things to note about Greenplum’s MR implementation:
- It’s very similar in form and expression to Google and Hadoop
- Extensions for Joins and Pipelined task execution
- Native parallel file access
- Parallelism is full and transparent to the programmer

In summary: we have implemented MapReduce within which you can write SQL, Perl, Python and many more languages. It is straightforward to use MR programs written for Hadoop or Google and port them to Greenplum.

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