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You're reading from  DynamoDB Cookbook

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Published inSep 2015
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ISBN-139781784393755
Edition1st Edition
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Tanmay Deshpande
Tanmay Deshpande
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Tanmay Deshpande

Tanmay Deshpande is a Hadoop and big data evangelist. He currently works with Schlumberger as a Big Data Architect in Pune, India. He has interest in a wide range of technologies, such as Hadoop, Hive, Pig, NoSQL databases, Mahout, Sqoop, Java, cloud computing, and so on. He has vast experience in application development in various domains, such as oil and gas, finance, telecom, manufacturing, security, and retail. He enjoys solving machine-learning problems and spends his time reading anything that he can get his hands on. He has great interest in open source technologies and has been promoting them through his talks. Before Schlumberger, he worked with Symantec, Lumiata, and Infosys. Through his innovative thinking and dynamic leadership, he has successfully completed various projects. He regularly blogs on his website http://hadooptutorials.co.in. You can connect with him on LinkedIn at https://www.linkedin.com/in/deshpandetanmay/. He has also authored Mastering DynamoDB, published in August 2014, DynamoDB Cookbook, published in September 2015, Hadoop Real World Solutions Cookbook-Second Edition, published in March 2016, Hadoop: Data Processing and Modelling, published in August, 2016, and Hadoop Blueprints, published in September 2016, all by Packt Publishing.
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Compressing large data before storing it in DynamoDB


We are all aware of DynamoDB's storage limitations for the item's size. Suppose that we get into a situation where storing large attributes in an item is a must. In that case, it's always a good choice to compress these attributes, and then save them in DynamoDB. In this recipe, we are going to see how to compress large items before storing them.

Getting ready

To get started with this recipe, you should have your workstation ready with Eclipse or any other IDE of your choice.

How to do it…

There are numerous algorithms with which we can compress the large items, for example, GZIP, LZO, BZ2, and so on. Each algorithm has a trade-off between the compression time and rate. So, it's your choice whether to go with a faster algorithm or with an algorithm, that provides a higher compression rate.

Consider a scenario in our e-commerce website, where we need to save the product reviews written by various users. For this, we created a ProductReviews...

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DynamoDB Cookbook
Published in: Sep 2015Publisher: ISBN-13: 9781784393755

Author (1)

author image
Tanmay Deshpande

Tanmay Deshpande is a Hadoop and big data evangelist. He currently works with Schlumberger as a Big Data Architect in Pune, India. He has interest in a wide range of technologies, such as Hadoop, Hive, Pig, NoSQL databases, Mahout, Sqoop, Java, cloud computing, and so on. He has vast experience in application development in various domains, such as oil and gas, finance, telecom, manufacturing, security, and retail. He enjoys solving machine-learning problems and spends his time reading anything that he can get his hands on. He has great interest in open source technologies and has been promoting them through his talks. Before Schlumberger, he worked with Symantec, Lumiata, and Infosys. Through his innovative thinking and dynamic leadership, he has successfully completed various projects. He regularly blogs on his website http://hadooptutorials.co.in. You can connect with him on LinkedIn at https://www.linkedin.com/in/deshpandetanmay/. He has also authored Mastering DynamoDB, published in August 2014, DynamoDB Cookbook, published in September 2015, Hadoop Real World Solutions Cookbook-Second Edition, published in March 2016, Hadoop: Data Processing and Modelling, published in August, 2016, and Hadoop Blueprints, published in September 2016, all by Packt Publishing.
Read more about Tanmay Deshpande