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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 ...
Scala is a pure object-oriented language in the sense that every value is an object. Data types and behaviors of objects are described by classes and traits. Class abstractions are extended by subclassing and by a flexible mixin-based composition mechanism to avoid the problems of multiple inheritance. Traits are Scala's replacement for Java's ...
SPARK is a formally defined computer programming language based on the Ada language, intended for developing high integrity software used in systems where predictable and highly reliable operation is essential. It facilitates developing applications that demand safety, security, or business integrity.
This article lists concurrent and parallel programming languages, categorizing them by a defining paradigm.Concurrent and parallel programming languages involve multiple timelines.
Apache Flink: Java/Scala library that allows streaming (and batch) computations to be run atop a distributed Hadoop (or other) cluster; Apache Spark; SystemC: Library for C++, mainly aimed at hardware design. TensorFlow: A machine-learning library based on dataflow programming.
For large scale hypergraphs, a distributed framework [7] built using Apache Spark is also available. It can be desirable to study hypergraphs where all hyperedges have the same cardinality; a k-uniform hypergraph is a hypergraph such that all its hyperedges have size k .
Doris: MPP-based interactive SQL data warehousing for reporting and analysis, good for both high-throughput scenarios and high-concurrency point queries; Drill: software framework that supports data-intensive distributed applications for interactive analysis of large-scale datasets; Druid: high-performance, column-oriented, distributed data store
In programming language theory, lazy evaluation, or call-by-need, [1] is an evaluation strategy which delays the evaluation of an expression until its value is needed (non-strict evaluation) and which avoids repeated evaluations (by the use of sharing).