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Spark Core is the foundation of the overall project. It provides distributed task dispatching, scheduling, and basic I/O functionalities, exposed through an application programming interface (for Java, Python, Scala, .NET [16] and R) centered on the RDD abstraction (the Java API is available for other JVM languages, but is also usable for some other non-JVM languages that can connect to the ...
In the past, many of the implementations use the Apache Hadoop platform, however today it is primarily focused on Apache Spark. [3] [4] Mahout also provides Java/Scala libraries for common math operations (focused on linear algebra and statistics) and primitive Java collections. Mahout is a work in progress; a number of algorithms have been ...
Phalcon was created by Andrés Gutiérrez and collaborators looking for a new approach to traditional web application frameworks written in PHP. The original draft of the framework in 2011 was called "Spark", [6] the name was later changed to Phalcon, representing the words "PHP" and "falcon". Phalcon's initial release was made available on ...
It using the hadoop file system as distributed storage. Tiles: templating framework built to simplify the development of web application user interfaces. Trafodion: Webscale SQL-on-Hadoop solution enabling transactional or operational workloads on Apache Hadoop [11] [12] [13] Tuscany: SCA implementation, also providing other SOA implementations
The Hadoop distributed file system (HDFS) is a distributed, scalable, and portable file system written in Java for the Hadoop framework. Some consider it to instead be a data store due to its lack of POSIX compliance, [36] but it does provide shell commands and Java application programming interface (API) methods that are similar to other file ...
Apache Parquet is a free and open-source column-oriented data storage format in the Apache Hadoop ecosystem. It is similar to RCFile and ORC, the other columnar-storage file formats in Hadoop, and is compatible with most of the data processing frameworks around Hadoop.
Cascading is a software abstraction layer for Apache Hadoop and Apache Flink. Cascading is used to create and execute complex data processing workflows on a Hadoop cluster using any JVM-based language (Java, JRuby, Clojure, etc.), hiding the underlying complexity of MapReduce jobs. It is open source and available under the Apache License.
Impala is integrated with Hadoop to use the same file and data formats, metadata, security and resource management frameworks used by MapReduce, Apache Hive, Apache Pig and other Hadoop software. Impala is promoted for analysts and data scientists to perform analytics on data stored in Hadoop via SQL or business intelligence tools. The result ...