Search results
Results from the WOW.Com Content Network
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 ...
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.
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 ...
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 ...
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
Presto (including PrestoDB, and PrestoSQL which was re-branded to Trino) is a distributed query engine for big data using the SQL query language. Its architecture allows users to query data sources such as Hadoop, Cassandra, Kafka, AWS S3, Alluxio, MySQL, MongoDB and Teradata, [1] and allows use of multiple data sources within a query.
Its primary use is in Apache Hadoop, where it can provide both a serialization format for persistent data, and a wire format for communication between Hadoop nodes, and from client programs to the Hadoop services. Avro uses a schema to structure the data that is being encoded.
It can also be integrated into Data Flow frameworks like Apache Spark, Apache Hadoop, and Apache Flink using the abstracted Rabit [13] and XGBoost4J. [14] XGBoost is also available on OpenCL for FPGAs. [15] An efficient, scalable implementation of XGBoost has been published by Tianqi Chen and Carlos Guestrin. [16]