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How to Work With Tuple in Python

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Tuple in python is one of the streaming datasets. The other streaming datasets are List and Dictionary. Operations that you can perform on it are shown here for your reference. Writing tuple is easy. It has values of comma separated, and enclosed with parenthesis '()'. The values in the tuple are immutable, which means you cannot replace with new values. #1. How to create a tuple Code: Tuple example my_tuple=(1,2,3,4,5) print(my_tuple) Output: (1, 2, 3, 4, 5) ** Process exited - Return Code: 0 ** Press Enter to exit terminal #2. How to read tuple values Code: print(my_tuple[0]) Output: 1 ** Process exited - Return Code: 0 ** Press Enter to exit terminal #3. How to add two tuples Code: a=(1,6,7,8) c=(3,4,5,6,7,8) d=print(a+c) Output: (1, 6, 7, 8, 3, 4, 5, 6, 7, 8) ** Process exited - Return Code: 0 ** Press Enter to exit terminal #4.  How to count tuple values Here the count is not counting values; count the repetition of a given value. Code: sample=(1, 6, 7, 8, 3, 4, 5, 6, 7, 8
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SPARK is Replacement for MapReduce in Bigdata Real Analytics!

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Apache Spark is among the Hadoop ecosystem technologies acting as catalysts for broader adoption of big data infrastructure. Now, Looker -- a vendor of business intelligence software -- has announced support for Spark and other Hadoop technologies. The goal? To speed up access to the data that fuels business decision making.
SPARK Vs MapReduce
SPARK Jobs

Hadoop's arrival on the scene 10 years ago may have started the big data revolution, but only recently did adoption of this technology begin spreading to a wider audience. Apache Spark is one of the catalysts for the growing adoption rates.

Spark can be used as a replacement for MapReduce, a component of Hadoop implementations, to speed up the processing and analytics of big data by 100x in memory, according to the Apache Software Foundation.

In today's business environment, in which real-time analytics is the goal and organizations don't want to wait for data warehouses and analysts to provide batch intelligence back to business users, Spark has gained momentum.

And here's one case in point: Looker, a business intelligence platform used by Avant, Acorns, and Etsy, this week announced support for Presto and Spark SQL. The company also updated its support for Impala and Hive, other Hadoop ecosystem technologies that speed up analysis on Hadoop.

Looker's announcement of support for these additional Hadoop ecosystem technologies lets organizations "leave data in Hadoop and process it at speed and at scale," said James Haight,

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