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Category: Spark

how to read json in pyspark dataframe
Spark

Handling Nested JSON data in PySpark

What is JSON? JSON, or JavaScript Object Notation, is a lightweight data-interchange format for exchanging data between different systems. It is language-independent, meaning it can

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April 5, 2023 No Comments
Kryo Serializer in PySpark: How to Get the Most Out of Your Data
Spark

Kryo Serializer in PySpark: How to Get the Most Out of Your Data

The Kryo serializer in PySpark is a powerful tool that can help you get the most out of your data. By using the Kryo serializer,

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March 8, 2023 No Comments
9 Ways to Improve the Performance of Your Apache Spark Scripts in Python
Spark

9 Ways to Improve the Performance of Your Apache Spark Scripts in Python

Are you looking for ways to improve the performance of your Apache Spark scripts in Python? Apache Spark is an amazing technology for data processing,

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February 4, 2023 No Comments
Spark

Managing small file issues when writing to Hive with Spark SQL

Small files in Apache Spark and Hadoop can cause a huge performance bottleneck, as the processing of these files requires extra computational resources and processing

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May 15, 2021 No Comments
Spark

Improving performance when calculating percentiles in Spark

Performance is a major concern when you’re working in a distributed environment with a massive amount of data. I’ve discussed Spark performance in quite a

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April 2, 2021 No Comments
Spark

Overcoming Futures Timeout & Read Timeout errors in PySpark

This article covers a less than orthodox method for handling resource constraints in your PySpark code. Consider the below scenario. Here, we are loading data

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March 6, 2021 No Comments
Spark

Handling data skew / imbalanced partitions in Pyspark

Data Skew is a real problem in Spark. It seems like the sort of thing which should be solved automatically by the job manager but

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January 24, 2021 No Comments
Spark

Achieving optimial performance for your Spark jobs through config changes

Apache Spark provides us with a framework to crunch a huge amount of data efficiently by leveraging parallelism which is great! However, with great power,

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January 23, 2021 2 Comments
Spark

A comprehensive guide to windowing functions in PySpark for data science

Window functions are incredibly useful. Within a single query, you can find out things which may have otherwise been tricky. In this article, I will

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January 17, 2021 No Comments
Spark

A crash course in UDF’s in Pyspark

Okay, so the first thing I should note is that you should avoid UDF’s (User Defined Functions) like the plague unless you absolutely have to;

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June 10, 2020 No Comments
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