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  1. pyspark.SparkContext.parallelize — PySpark 4.1.1 documentation

    pyspark.SparkContext.parallelize # SparkContext.parallelize(c, numSlices=None) [source] # Distribute a local Python collection to form an RDD. Using range is recommended if the input represents a range …

  2. PARALLELIZE Definition & Meaning - Merriam-Webster

    The meaning of PARALLELIZE is to make parallel. How to use parallelize in a sentence.

  3. PySpark parallelize () – Create RDD from a list data

    Feb 23, 2025 · PySpark parallelize () is a function in SparkContext and is used to create an RDD from a list collection. In this article, I will explain the usage of

  4. PARALLELIZE definition and meaning | Collins English Dictionary

    2 meanings: 1. to draw parallels or points of similarity between (two things) 2. to make or place parallel to (something).... Click for more definitions.

  5. parallelize - Wiktionary, the free dictionary

    Dec 14, 2025 · To treat as if parallel; to draw parallels between. They erroneously parallelized the symptoms of the two diseases.

  6. parallelize, v. meanings, etymology and more | Oxford English Dictionary

    There are six meanings listed in OED's entry for the verb parallelize, two of which are labelled obsolete. See ‘Meaning & use’ for definitions, usage, and quotation evidence.

  7. parallelize - Definition, Meaning & Synonyms - Vocab Dictionary

    To make a process or operation simultaneous, often to improve efficiency and speed.

  8. PARALLELIZE Definition & Meaning | Dictionary.com

    PARALLELIZE definition: to make parallel; place so as to be parallel. See examples of parallelize used in a sentence.

  9. What Does Parallelize Mean | Dagster

    Learn what Parallelize means and how it fits into the world of data, analytics, or pipelines, all explained simply.

  10. What does parallelize mean? - Definitions.net

    Parallelize generally refers to the process of converting a piece of sequential program or algorithm into a parallel form that can be executed simultaneously on multiple processors or cores, in order to …