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  2. Apache Spark - Wikipedia

    en.wikipedia.org/wiki/Apache_Spark

    The Dataframe API was released as an abstraction on top of the RDD, followed by the Dataset API. In Spark 1.x, the RDD was the primary application programming interface (API), but as of Spark 2.x use of the Dataset API is encouraged [3] even though the RDD API is not deprecated. [4] [5] The RDD technology still underlies the Dataset API. [6] [7]

  3. Dask (software) - Wikipedia

    en.wikipedia.org/wiki/Dask_(software)

    Dask delayed [20] is an interface used to parallelize generic Python code that does not fit into high level collections like Dask Array or Dask DataFrame. Python functions decorated with Dask delayed adopt a lazy evaluation strategy by deferring execution and generating a task graph with the function and its arguments.

  4. Dataframe - Wikipedia

    en.wikipedia.org/wiki/Dataframe

    Dataframe may refer to: A tabular data structure common to many data processing libraries: pandas (software) § DataFrames; The Dataframe API in Apache Spark;

  5. Group by (SQL) - Wikipedia

    en.wikipedia.org/wiki/Group_by_(SQL)

    A GROUP BY statement in SQL specifies that a SQL SELECT statement partitions result rows into groups, based on their values in one or several columns. Typically, grouping is used to apply some sort of aggregate function for each group. [1] [2] The result of a query using a GROUP BY statement contains one row for

  6. Determining the number of clusters in a data set - Wikipedia

    en.wikipedia.org/wiki/Determining_the_number_of...

    The average silhouette of the data is another useful criterion for assessing the natural number of clusters. The silhouette of a data instance is a measure of how closely it is matched to data within its cluster and how loosely it is matched to data of the neighboring cluster, i.e., the cluster whose average distance from the datum is lowest. [8]

  7. Aggregate function - Wikipedia

    en.wikipedia.org/wiki/Aggregate_function

    Aggregate functions present a bottleneck, because they potentially require having all input values at once.In distributed computing, it is desirable to divide such computations into smaller pieces, and distribute the work, usually computing in parallel, via a divide and conquer algorithm.

  8. MapReduce - Wikipedia

    en.wikipedia.org/wiki/MapReduce

    MapReduce is a programming model and an associated implementation for processing and generating big data sets with a parallel and distributed algorithm on a cluster. [1] [2] [3]A MapReduce program is composed of a map procedure, which performs filtering and sorting (such as sorting students by first name into queues, one queue for each name), and a reduce method, which performs a summary ...

  9. Method chaining - Wikipedia

    en.wikipedia.org/wiki/Method_chaining

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