HadoopDB provides a parallel database front-end to data analysts enabling them to process SQL queries The SMS planner extends Hive [11] Hive transforms
hadoopdb
22 jan 2015 · 22/1/15 Emmanuel Gangler – Workshop Mastodons 8/16 Quelques résultats (3) Focus Expérimentation sous Hive et HadoopDB : Synthèse
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HadoopDB is a hybrid of MapReduce and DBMS technolo- gies, designed to meet tends Hive [9] to provide a SQL interface to HadoopDB See our previous
hadoopdb demo
There is a map and a reduce phase in these queries HadoopDB pushes the SQL operators' execution in to the PostGreSQL Using Hive's query optimizer
Chalamalla HadoopDB
is 2-63 times faster than existing indexes in Hive, 2-94 times faster than HadoopDB, 2-75 times faster than scanning the whole table in different query selectivity
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results demonstrate both performance and scalability advantage of SQLMR compared to MySQL and two NoSQL data processing systems, Hive and HadoopDB
SQLMR A Scalable Database Management System for Cloud Computing
22 janv. 2015 Colloque Mastodons CNRS
21 mai 2015 HaoLap and compares that with Hive HadoopDB
HadoopDB is a hybrid of MapReduce and DBMS technolo- gies designed to meet the growing demand of tends Hive [9] to provide a SQL interface to HadoopDB.
23 janv. 2014 Hive vs HadoopDB. – Hive > HadoopDB. ? Sélection avec index. ? Group by sur requêtes non sélectives (Hadoop ne profite pas des.
Hence we use PostgreSQL as the database layer and Hadoop as the communication layer
HadoopDB provides a parallel database front-end to data analysts enabling them to process SQL queries. The SMS planner extends Hive [11].
16 juin 2011 featuring a SQL interface (Hive). We show that HadoopDB successfully competes with other systems. Categories and Subject Descriptors.
Across a variety of data process- ing tasks HadoopDB outperformed simple SQL-into-. MapReduce translation layers (such as Hive)
Across a variety of data process- ing tasks HadoopDB outperformed simple SQL-into-. MapReduce translation layers (such as Hive)
multidimensional data model. Some practical data warehouses based on Hadoop have emerged such as Hive HadoopDB and HBase. Hive
Gestion et exploration des grandes masses de données