Apache Spark

Apache Spark Tutorial

Replacing String Values in Spark with regexp_replace

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Apache Spark is one of the most widely used open-source distributed computing systems that offers an interface for programming entire clusters with implicit data parallelism and fault tolerance. Spark has built-in modules for streaming, SQL, machine learning, and graph processing, which allows for complex analytical applications to be written seamlessly across different workloads. One of …

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Reading and Writing Parquet Files from Amazon S3 with Spark

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Apache Spark has gained prominence in the world of big data processing due to its ability to handle large-scale data analytics in a distributed computing environment. Spark provides native support for various data formats, including Parquet, a columnar storage format that offers efficient data compression and encoding schemes. Reading from and writing to Parquet files …

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Working with ArrayType in Spark DataFrame Columns

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When working with Apache Spark, handling complex data structures such as arrays becomes a common task, especially in data processing and transformation operations. The ArrayType is one of the data types available in Spark for dealing with collections of elements in columns of a DataFrame. In this comprehensive guide, we’ll explore how to work with …

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