Big Data Analytics for Non-Programmers
Download as PPTX, PDF4 likes1,234 views
The document discusses tools for working with big data without needing to know Java. It states that Hadoop can be learned without Java through tools like Pig and Hive that provide high-level languages. Pig uses Pig Latin to simplify complex MapReduce programs, allowing data operations like filters, joins and sorting with only 10 lines of code compared to 200 lines of Java. Hive also does not require Java knowledge, defining a SQL-like language called HiveQL to query and analyze stored data. The document promotes these tools as alternatives to writing custom MapReduce code in Java for non-programmers working with big data.
Big Data Analytics for Non-Programmers
- 1. wwww.edureka.co/big-data-and-hadoop Big Data Analytics for Non-Programmers
- 2. wwww.edureka.co/big-data-and-hadoop Agenda for the day Can Hadoop be learnt without knowing Java? How Pig can be used in place of MapReduce ? Querying data with HiveQL
- 3. wwww.edureka.co/big-data-and-hadoop Can Hadoop be learnt without knowing Java?
- 4. wwww.edureka.co/big-data-and-hadoop YES !! Hadoop can be learnt without knowing Java
- 5. wwww.edureka.co/big-data-and-hadoop Pig & Hive Tools like Pig and Hive that are built on top of Hadoop, offer high-level languages for working with data If you want to write MapReduce program, then you can use Pig and Pig Latin for which knowledge of Java is not required. If you want to view data in HDFS in a readable form you can use Hive which again does not require any knowledge of Java.
- 7. wwww.edureka.co/big-data-and-hadoop But why Pig? Pig simplifies complex MapReduce programs by using Pig Latin Additionally, If you want to write your own MapReduce code, you can do so in any language (e.g. Perl, Python, Ruby, C, etc.) But the most attractive features of Pig are: 10 lines of PIG = 200 lines of Java Built in operations like: Join Group Filter Sort and more…
- 8. wwww.edureka.co/big-data-and-hadoop Why Pig? Provides common data operations filters, joins, ordering, etc. and nested data types tuples, bags, and maps missing from MapReduce. It is Open source and is actively supported by a community of developers. Structured data Semi-Structured data Unstructured data Similar to SQL Reads like a series of steps Java Python JavaScript Ruby An ad-hoc way of creating and executing map-reduce jobs on very large data sets Can take any data Easy to learn, Easy to read and write Extensible by UDF (User Defined Functions) Java not required
- 10. wwww.edureka.co/big-data-and-hadoop Why Hive? Defines SQL-Like Query Language called HiveQL Data Warehouse Infrastructure Allows programmers to plug-in custom mappers and reducers Provides tools to enable easy ETL
- 11. wwww.edureka.co/big-data-and-hadoop Features of Hive You can use HIVE to read and write files on Hadoop and run your reports from a BI tool Predictive Modeling & Hypothesis Testing Document Indexing Customer-facing Business Intelligence Log Processing Data Mining HIVE Applications
- 13. wwww.edureka.co/big-data-and-hadoop Thank You Questions/Queries/Feedback Recording and presentation will be made available to you within 24 hours