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Bucketing in Hive

With Bucketing in Hive, we can group similar kinds of data and write it to one single file. This allows better performance while reading data & when joining two tables.

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Alter Table Partitions in Hive

We have created partitioned tables, inserted data into them. Now, we will learn how to drop some partition or add a new partition to the table in hive.

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Static vs Dynamic Partitioning in Hive

Hive supports Static and Dynamic Partitions. Let us understand what is difference between them and their use cases.

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Partitioning in Hive

Using Partitioning, We can increase hive query performance. But if we do not choose partitioning column correctly it can create small file issue.

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Adding Custom Schema to Spark Dataframe

We will learn how to specify our custom schema with column names and data types for Spark data frames.

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Reading data from a file in Spark

We will learn how to load data from JSON, CSV, TSV, Pipe Delimited or any other type for delimited file to spark Dataframe.

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Hive Data Manipulation - Loading Data to Hive Tables

We will learn how to load and populate data to hive table. We will also learn how to copy data to hive tables from local system.

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Create, Alter, Delete Tables in Hive

We will learn how to create Hive tables, also altering table columns, adding comments and table properties and deleting Hive tables.

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Creating Database in Hive

We will learn how to create databases in Hive with simple operations like listing database, setting database location in HDFS & deleting database.

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Data Types in Hive

Hive supports multiple data types like SQL. On top of that, there are multiple complex data types in hive which makes it easy to process data in Hive.

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External Vs Internal(Managed) Tables in Hive

Hive has two types of tables, external and managed. In this blog, we will learn about them and decide which use case is suitable for each table.

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Set, Get and Delete AWS S3 bucket policies

In this blog, we are going to learn how to get, put and delete S3 bucket policies suing S3 Console as well as programmatically using AWS CLI & Python

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