Apache Hive is a type of data warehouse tool used for data analysis and data query. It works on SQL interface in order to query the stored data in different file systems and databases assimilated with Hadoop. While pursuing the HIVE courses, students learn about various topics such as Hive, Hive DDL, Hive DML, Hive function, operators, and more, but the only thing that remains the same is an assignment. Generally, assignments are given to check a student's potential and subject-knowledge. Therefore, it is important to prepare a unique paper covering all the details of the assignment. You can also contact us for Hive assignment help if you get stuck at any point.
We have a pool of HIVE professionals who have been helping students with their HIVE assignment tasks since the last 8 years. Thus, they have a complete understanding and knowledge to deal with hive assignments. Additionally, our experts offering hive assignment help for Australian university students are skilled in big data, Apache Hadoop, SQL, and Linux, which can be asked to use in your assignments.
It comprises various important terms like data types, creating a database, creating a table, partitioning, dropping tables, Hive QL, etc. Being a student, you might be aware that hive was initially developed by Facebook, and later on, it was taken up by Apache Software Foundation and developed it as Apache Hive. Nowadays, it is being used by various companies including Amazon. It is comprised of the following features:
Under the study of Hive courses, you are required to deal with several assignments. These assignments can be based on any topic such as architecture, working, creating a table, and more. Here's a HIVE assignment sample was recently written by our HIVE expert:
These are the initial two tasks that students are required to answer in CN7022 coursework. Similarly, there are a few more tasks to complete. To complete both the parts of the assignment, you must have adequate subject-knowledge and academic writing skills. You must follow the assessor's instructions and guidelines while writing this assignment. If you need help in writing your hive assignments, then Online Assignment Expert can be the best choice. Do fill the form along with the details where you need and our expert will soon be there to resolve your queries.
The below-given diagram shows the hive architecture. Let's see.
In this picture, you can clearly see a few essential components such as user interfaces, Web UI, Hive Command line, HD insight, Meta Store, and a few more.
User Interface: Apache hive software can easily make the interaction between HDFS and user. It is compatible with the following user interface: Hive command line; Hive Web UI; and Hive HDInsight.
Meta Store: Apache Hive selects a particular database server in order to preserve the metadata or schema of tables, columns of a table, data types, databases, and HDFS mapping.
Execution Engine: Execution engine is termed as the conjunction part of MapReduce and HiveQL process Engine. It is used for the querying process and getting results just like the MapReduce results.
HiveQL Process Engine: This process engine is quite the same as to SQL used for querying schema info. Our Hive assignments help experts say HiveQL has replaced the traditional approach followed for the MapReduce program. Initially, the MapReduce program was used to be written in Java, but now it is written in a query for a MapReduce job.
To know more about how we write assignments on hive architecture processes or its related terms, feel free to chat with our hive assignment makers.
The diagram attached below by our hive assignment help experts explains the workflow between Hadoop and Hive.
Now, we will understand how Hive/Hadoop interacts with Hadoop/Hive framework.
Execute Query: The WEBUI and Command-Line give a query to the database driver in order to execute.
Get Plan: Drivers like ODBC and JDBC need assistance from the query compiler to query plan and check syntax.
Send Plan: Here, the compiler is used to check the requirement and re-pass that particular plan back to the driver.
Execute plan and Job: Now, after following the above steps, it is the time to execute the job. The execution engine transmits the job to Job Tracker, and then it is assigned to Task Tracker.
Fetch Result: After this, the user gets the results and again it is sent to the driver and driver resends it to hive interface.
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