Apache Spark installation guides, performance tuning tips, general tutorials, etc.

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Data partitioning is critical to data processing performance especially for large volume of data processing in Spark. Partitions in Spark won’t span across nodes though one node can contains more than one partitions. When processing, Spark assigns one task for each partition and each worker threads ...

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This post shows how to derive new column in a Spark data frame from a JSON array string column. I am running the code in Spark 2.2.1 though it is compatible with Spark 1.6.0 (with less JSON SQL functions). Refer to the following post to install Spark in Windows. Install Spark 2.2.1 in Windows ...

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In Spark, SparkContext.parallelize function can be used to convert Python list to RDD and then RDD can be converted to DataFrame object. The following sample code is based on Spark 2.x. In this page, I am going to show you how to convert the following list to a data frame: data = [('Category A' ...

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From Spark 2.0, you can easily read data from Hive data warehouse and also write/append new data to Hive tables. This page shows how to operate with Hive in Spark including: Create DataFrame from existing Hive table Save DataFrame to a new Hive table Append data to the existing Hive table via ...

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Spark is an analytics engine for big data processing. There are various ways to connect to a database in Spark. This page summarizes some of common approaches to connect to SQL Server using Python as programming language. For each method, both Windows Authentication and SQL Server ...

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In this page, I’m going to demonstrate how to write and read parquet files in Spark/Scala by using Spark SQLContext class. Go the following project site to understand more about parquet. https://parquet.apache.org/ If you have not installed Spark, follow this page to setup: Install Big Data ...

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Spark provides rich APIs to save data frames to many different formats of files such as CSV, Parquet, Orc, Avro, etc. CSV is commonly used in data application though nowadays binary formats are getting momentum. In this article, I am going to show you how to save Spark data frame as CSV file in ...

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In my previous post, I demonstrated how to write and read parquet files in Spark/Scala. The parquet file destination is a local folder. Write and Read Parquet Files in Spark/Scala In this page, I am going to demonstrate how to write and read parquet files in HDFS. import ...

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This article shows how to convert a Python dictionary list to a DataFrame in Spark using Python. data = [{"Category": 'Category A', "ID": 1, "Value": 12.40}, {"Category": 'Category B', "ID": 2, "Value": 30.10}, {"Category": 'Category C', "ID": 3, "Value": 100.01} ] The ...

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For SQL developers that are familiar with SCD and merge statements, you may wonder how to implement the same in big data platforms, considering database or storages in Hadoop are not designed/optimised for record level updates and inserts. In this post, I’m going to demonstrate how to implement ...