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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 ...
Apache Hadoop (/ h ə ˈ d uː p /) is a collection of open-source software utilities for reliable, scalable, distributed computing.It provides a software framework for distributed storage and processing of big data using the MapReduce programming model.
Apache Iceberg is a high performance open-source format for large analytic tables.Iceberg enables the use of SQL tables for big data while making it possible for engines like Spark, Trino, Flink, Presto, Hive, Impala, StarRocks, Doris, and Pig to safely work with the same tables, at the same time. [1]
It has also been argued RDBMSs offer out of the box support for column-storage, working with compressed data, indexes for efficient random data access, and transaction-level fault tolerance. [10] Pig Latin is procedural and fits very naturally in the pipeline paradigm while SQL is instead declarative. In SQL users can specify that data from two ...
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 ...
CarbonData: an indexed columnar data format for fast analytics on big data platform, e.g., Apache Hadoop, Apache Spark, etc; Cassandra: highly scalable second-generation distributed database; Causeway(formerly Isis): a framework for rapidly developing domain-driven apps in Java; Cayenne: Java ORM framework
Dask is an open-source Python library for parallel computing.Dask [1] scales Python code from multi-core local machines to large distributed clusters in the cloud. Dask provides a familiar user interface by mirroring the APIs of other libraries in the PyData ecosystem including: Pandas, scikit-learn and NumPy.
[7] [8] This aims to make analytics more suitable for business analyst level staff, like sales and other departments using the data, rather than requiring a "data engineer" or "data scientist" who understands languages like MapReduce or Pig. [2] [9] [10] Dan Udoutch serves as president and CEO of Alpine Data Labs. [11]