Partitioning in Hive – Hadoop Online Tutorials

What is Hive Partition?

Hive Partitions is a way to organize tables into partitions. In Apache, it is done by dividing tables into different parts based on the partition keys. This is used when a table has one or many partition keys. Partition keys are the basic elements for shaping how the data is stored in a table.

Why Hive Partition is needed:

The Hive Partition was introduced to make the process of data querying easy. The Apache Hive reads the full dataset when we submit a SQL query and then submits it to a cluster. Apache Hive makes the partitions very easy by creating partitions by its partition method at the time of table creation. In this method, all the table data is divided into many partitions and each partition matches to a specific value of partition column. So it reduces the input and output time which is required by the query. As a result of this, the performance speed will be increased.

Types of Hive Partition:

There are two types of Hive Map. They are

Static Partition

Dynamic Partition

Static Partition:

If we insert data files one by one into a partition table, it is called Static Partition. While loading big files into the hive table static partition is preferred. The partition also helps in saving our time in loading data. This is because here we add a partition statically in the table and move the file into the partition of the table and also we can alter it. This static partition will also be in Strict Mode. It can be performed in the Hive manage table or in an external table too.

Dynamic Partition:

Dynamic Partition is the single insertion into a partition table. This partition loads the data from a non-partitioned table. But this Dynamic Partition takes much more time in loading all the data when we compare it to static partition. When there is a large data to be stored in a table this dynamic partition is very useful. It is also useful when we do not know how many columns are to be partitioned. Here we cannot alter the Dynamic Partition.

Advantages of Hive Partition:

This distributes all the elements horizontally

If there is a low volume of data a very fast execution takes place and hence time can be saved.

Disadvantages of Hive Partition:

Here searching a single record in the entire table is very difficult.

If there are many directories too manysmall partitions will be made

If there is a high volume of data it is very difficult to handle as it takes a very long time for execution.

Pig interview questions:

In Apache, Pig, it is an Apache open-source project and spark partitions will be there for qualifying a better developer. This Apache pig can be either in local mode or in a cluster mode. To start Apache Pig in a local mode, the option “-x local” should be used. If no option is stated then by default it will be started in the cluster mode.