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You're reading from  Big Data Analysis with Python

Product typeBook
Published inApr 2019
Reading LevelIntermediate
PublisherPackt
ISBN-139781789955286
Edition1st Edition
Languages
Python
Tools
MatplotlibHadoop
Concepts
Data Visualization
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Authors (3):
Ivan Marin
Ivan Marin
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Ivan Marin

Ivan Marin is a systems architect and data scientist working at Daitan Group, a Campinas-based software company. He designs big data systems for large volumes of data and implements machine learning pipelines end to end using Python and Spark. He is also an active organizer of data science, machine learning, and Python in So Paulo, and has given Python for data science courses at university level.
Read more about Ivan Marin

Ankit Shukla
Ankit Shukla
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Ankit Shukla

Ankit Shukla is a data scientist working with World Wide Technology, a leading US-based technology solution provider, where he develops and deploys machine learning and artificial intelligence solutions to solve business problems and create actual dollar value for clients. He is also part of the company's R&D initiative, which is responsible for producing intellectual property, building capabilities in new areas, and publishing cutting-edge research in corporate white papers. Besides tinkering with AI/ML models, he likes to read and is a big-time foodie.
Read more about Ankit Shukla

Sarang VK
Sarang VK
author image
Sarang VK

Sarang VK is a lead data scientist at StraitsBridge Advisors, where his responsibilities include requirement gathering, solutioning, development, and productization of scalable machine learning, artificial intelligence, and analytical solutions using open source technologies. Alongside this, he supports pre-sales and competency.
Read more about Sarang VK

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Writing Parquet Files

The Parquet data format (https://parquet.apache.org/) is binary, columnar storage that can be used by different tools, including Hadoop and Spark. It was built to support compression, to enable higher performance and storage use. Its column-oriented design helps with data selection for performance, as only the data in the required columns are retrieved, instead of searching for the data and discarding values in rows that are not required, reducing the retrieval time for big data scenarios, where the data is distributed and on disk. Parquet files can also be read and written by external applications, with a C++ library, and even directly from pandas.

The Parquet library is currently being developed with the Arrow project (https://arrow.apache.org/).

When considering more complex queries in Spark, storing the data in Parquet format can increase performance, especially when the queries need to search a massive dataset. Compression helps to decrease the data volume that needs...

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Big Data Analysis with Python
Published in: Apr 2019Publisher: PacktISBN-13: 9781789955286
© 2019 Packt Publishing Limited All Rights Reserved

Authors (3)

author image
Ivan Marin

Ivan Marin is a systems architect and data scientist working at Daitan Group, a Campinas-based software company. He designs big data systems for large volumes of data and implements machine learning pipelines end to end using Python and Spark. He is also an active organizer of data science, machine learning, and Python in So Paulo, and has given Python for data science courses at university level.
Read more about Ivan Marin

author image
Ankit Shukla

Ankit Shukla is a data scientist working with World Wide Technology, a leading US-based technology solution provider, where he develops and deploys machine learning and artificial intelligence solutions to solve business problems and create actual dollar value for clients. He is also part of the company's R&D initiative, which is responsible for producing intellectual property, building capabilities in new areas, and publishing cutting-edge research in corporate white papers. Besides tinkering with AI/ML models, he likes to read and is a big-time foodie.
Read more about Ankit Shukla

author image
Sarang VK

Sarang VK is a lead data scientist at StraitsBridge Advisors, where his responsibilities include requirement gathering, solutioning, development, and productization of scalable machine learning, artificial intelligence, and analytical solutions using open source technologies. Alongside this, he supports pre-sales and competency.
Read more about Sarang VK

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