The main objective of this project is to learn about various database operations.
There 5 sub projects that help us in learning the various database operations:
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The required task for this sub project is to simulate data partitioning approaches on-top of an open source relational database management system (i.e., PostgreSQL) and then generate Python functions that load the input data into a relational table, partition the table using different horizontal fragmentation approaches, and insert new tuples into the right fragment.
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The required task is to build a simplified query processor that accesses data from the partitioned ratings table and write Python functions to perform the following operation RangeQuery() and PointQuery().
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The required task is to build a generic parallel sort and parallel join algorithm using Python.
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The required task is to write a map-reduce program that will perform equijoin. • The code should be in Java using Hadoop Framework. • The code would take two inputs, one would be the hdfs location of the file on which the equijoin should be performed and other would be the hdfs location of the file, where the output should be stored.
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The required task is to write two functions, which will perform some textual and spatial searching on MongoDB.