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#41

Apache Pig is ranked #41 in the Data Warehouse Tools product directory based on the latest available data collected by SelectHub. Compare the leaders with our In-Depth Report.

Apache Pig Benefits and Insights

Why use Apache Pig?

Key differentiators & advantages of Apache Pig

  • Robust Functionality and Extensibility: Offers a wide range of built-in functions; provides nested data types such as bags, maps, and tuples to handle concepts like missing data which are generally not found in MapReduce, the language it was built on. Also supports data-processing operations (i.e. filters, ordering, sorting, and joins) to conduct complex tasks. Alternatively, developers can program their own custom user-defined functions (UDFs) to tailor its functionality for business needs. 
  • Accessible Data Processing: Makes data processing and data mining accessible for users with limited knowledge in programming. Even novice developers with working knowledge in SQL can gain an advantage with its similarity to Pig Latin. 
  • Multi-Query Approach: Reduces the length of coding needed for operations, shortening developing time.  
  • Quicker Data Loads: Helps load data in any format, including unstructured data, quickly with ease. Reduces the time-consuming burden of data processing for large datasets. Leverage ETL (Extract, Transform, Load) to automate cleaning and importing of unstructured data. 

Industry Expertise

Largely used for data analysis by clients in multiple industries worldwide. These include IT and services, computer software, computer hardware, insurance, banking, higher education, hospital and healthcare, retail, and telecommunications.

Key Features

  • Optimization: Optimizes execution of tasks automatically; stay focused on the semantics of programming without worrying about efficiency. 
  • User-Defined Functions (UDFs): Supports defining custom functions in Java. Allows customization of processes such as data load, storage, aggregation and transformation. Besides Java, UDFs can be implemented in other programming languages such as Python, Jython, Ruby, Groovy and JavaScript. 
  • Built-in Functions: Without requiring registration and qualification processes, it includes these built-in functions:  
    • Dynamic Invokers: Ideal for static functions that do not accept arguments. Certain conditions may involve accepting a combination of doubles, ints, strings, arrays and floats with similar features.  
    • Eval Functions: Concatenate, compute and compare two or more similar types of expressions.  
    • Load/Store Functions: Determine the input and output of data with the help of load and store operators. 
    • Math Functions: Determine the absolute value, arc sine, arc cosine, cube root and arctangent of an expression. 
    • String Functions: Verify and make conclusive comparisons between two strings. 
    • Datetime Functions: Alter and manage data and time according to the given set of parameters.  
    • Tuple, Bag, Map Functions: Determine the conversion of two or more expressions into a tuple or bag.  
  • Pig Latin Language: Uses a procedural data flow language — compared to SQL which is declarative — which makes it easy to write programs for complex tasks that involve interrelated data transformation. 
  • Data Management: Analyzes all kinds of data — including structured, semi-structured and unstructured — and stores all the results in the Hadoop Distributed File System (HDFS).  
  • Client-Side: Operates on the client-side and not the server-side; does not support web interfaces.  

Limitations

At the time of this review, these are the limitations according to user feedback:

  •  Since it relies on ETL, it’s not an ideal choice for real-time data integration. 
  •  Does not offer a metadata database. 
  •  Doesn’t support thrift servers. 

Suite Support

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