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Apache Pig Reviews & Product Details

Apache Pig is a platform for analyzing large data sets that consists of a high-level language for expressing data analysis programs, coupled with infrastructure for evaluating these programs. The salient property of Pig programs is that their structure is amenable to substantial parallelization, which in turns enables them to handle very large data sets.

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The Apache Software Foundation

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Apache Pig Community

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Prashant V.

Enterprise (> 1000 emp.)

3/20/2020

"Apache Pig makes it easy to create efficient data pipelines"

4.5/5

What do you like best about Apache Pig?

Apache Pig and its query language (Pig Latin) allowed us to create data pipelines with ease. The language is designed to reflect the way data pipelines are designed, so it discards extraneous data, supports user defined functions (UDFs) , and offers a lot of control over the data flow. Review collected by and hosted on G2.com.

What do you dislike about Apache Pig?

Pig being a greedy language, will not evaluate data until it's actually needed. So errors are not visible unless you actually try to dump/print the data. There is no "debug" functionality to run the code in a dry-run mode. Review collected by and hosted on G2.com.

Recommendations to others considering Apache Pig:

Unless you already have implementations of Pig in the company that you are building on top of, you might be better off with other newer technologies with more Review collected by and hosted on G2.com.

What problems is Apache Pig solving and how is that benefiting you?

I have used Pig for data piplining and aggregation. The flow of the language reflects the flow of the data and so it is intuitive to understand what the data transformation is doing. However it hasn't kept up with the latest advances in technologies. If you were choosing a language, you would be better off with either Hive or Spark. Pig also has a steeper learning curve since it uses a proprietary language (Pig Latin). Review collected by and hosted on G2.com.

Prashanth K.

Big Data Engineer

Enterprise (> 1000 emp.)

4/18/2020

"Apache Pig has saved my life from forever coding!"

4.5/5

What do you like best about Apache Pig?

What I like best about Apache Pig how efficiently we can write any of our complex map reduce or spark jobs without having much deep knowledge of Java, Python, Groovy. Also, its easy to control the execution of job with the help of pig. Review collected by and hosted on G2.com.

What do you dislike about Apache Pig?

What I dislike about Apache Pig is its error debugging consume most of its development time as it can be some times immature/unstable. Also the support community is very much less when compared to that of hadoop mapreduce or spark issues. Review collected by and hosted on G2.com.

Recommendations to others considering Apache Pig:

For all of you who are facing writing complex mapreduce or spark jobs, you should definitely try pig Review collected by and hosted on G2.com.

What problems is Apache Pig solving and how is that benefiting you?

One of the problem which I was able to solve was, I was able to reduce latency using pig which was earlier observed while running spark jobs mainly due to optimization offered by Apache pig. Review collected by and hosted on G2.com.

Subhadipto P.

Engineer II

Enterprise (> 1000 emp.)

7/31/2018

"Useful for map reducing huge dataset - application in transportation engineering for probe data"

4.5/5

What do you like best about Apache Pig?

It can handle some of the simple mathematical operations, along with reducing the data. Aggregating the data is extremely useful. Running DateTime functionalities in apache pig is really a useful feature for faster and quicker results. Pig works on datasets of around 150 to 180 GB per month and reduces them efficiently within say 10 to 12 minutes. I would definitely recommend Apache pig to any basic coding person in the field of transportation engineering to start using Apache pig, especially when you need to handle huge dataset. Review collected by and hosted on G2.com.

What do you dislike about Apache Pig?

It cannot perform sequential operations, like taking consecutive lines and then comparing them. However, the workaround is to rank the segments, merge them and then perform the task. The main drawback still lies in the fact that it cannot be used to perform loops and nested loops across any variable(s). Hive might be a better choice in certain cases for that reason. Review collected by and hosted on G2.com.

Recommendations to others considering Apache Pig:

Reducing huge volume of data Review collected by and hosted on G2.com.

What problems is Apache Pig solving and how is that benefiting you?

Reducing speed data provided by INRIX to a monthly or a yearly aggregate. Pig is also utilized to calculate various existing traffic signals performances which were otherwise calculated using various small scale measures.

The main benefit of using pig on such operations is that any city agency can prepare the codes for once and run it throughout the city, or even they can extend it to a statewide level which will make it very efficient, quicker, and more reliable than the traditional way of handling them using SQL database Review collected by and hosted on G2.com.

Verified User in Research

Small-Business (50 or fewer emp.)

3/22/2020

Business partner of the seller or seller's competitor, not included in G2 scores.

"Apache Pig review by academica"

4/5

What do you like best about Apache Pig?

It is easy to learn and get into production. It automates important MapReduce tasks into SQL kind queries. Review collected by and hosted on G2.com.

What do you dislike about Apache Pig?

- Not all tasks in Big Data can be completed using pig. Review collected by and hosted on G2.com.

Verified User in Information Technology and Services

Enterprise (> 1000 emp.)

2/27/2020

"I have been using pig for aws Emr for Hadoop"

2.5/5

What do you like best about Apache Pig?

Ease of use and diversity. It is easy to be read Review collected by and hosted on G2.com.

What do you dislike about Apache Pig?

There are other languages developed having upper hand than pig Review collected by and hosted on G2.com.

Verified User in Computer Software

Enterprise (> 1000 emp.)

1/18/2019

"Apache Pig "

4.5/5

What do you like best about Apache Pig?

Less number of instructions does big tasks of collecting, loading, consolidating the data. Review collected by and hosted on G2.com.

What do you dislike about Apache Pig?

Not enough tools to debug

Incorrect/misleading exceptions Review collected by and hosted on G2.com.

Stirling N.

Reporting Manager

Government Administration

Enterprise (> 1000 emp.)

1/10/2018

"Apache Pig - Faster execution"

3.5/5

What do you like best about Apache Pig?

Apache Pig is a 1st pass compiler, which is at its best using DAG. Review collected by and hosted on G2.com.

What do you dislike about Apache Pig?

If you want to drill down and use complex structures, it is not the best way. Review collected by and hosted on G2.com.

Recommendations to others considering Apache Pig:

4 great purpose it is the right tool, finding out is, however a trickier business. Review collected by and hosted on G2.com.

What problems is Apache Pig solving and how is that benefiting you?

If you do not know the structure in advance, then DAG and declared execution plans may be the best way to find it out - then use SQL once the plan is know. Review collected by and hosted on G2.com.

Verified User in Marketing and Advertising

Mid-Market (51-1000 emp.)

3/24/2017

"Apache Pig"

4/5

What do you like best about Apache Pig?

1. Ease of use, its performance

2. MapReduce is fully abstracted

3. Ability to chain multiple MR jobs into a single Pig script

4. Allows you quickly to crank through big data to get some analytics done Review collected by and hosted on G2.com.

What do you dislike about Apache Pig?

1. Slower in performance compared to Spark

2. Less support e.g String concatenation only allows 2 at a time, cannot sort & filter inside Group BY, etc

3. Cannot read in other forms of input like csv as parquet, what Spark can do

4. Error handling needs to be better. Not easy to debug UDFs Review collected by and hosted on G2.com.

Recommendations to others considering Apache Pig:

Definitely a good starting point for writing quick big data applications. Anyone who has experience writing queries and basic programming experience in Java, should be able to pick it this language up in short time. Its really useful to learn and makes ad-hoc analytics very convenient. Review collected by and hosted on G2.com.

What problems is Apache Pig solving and how is that benefiting you?

Few of our proprietary data pipelines involving batch-processing are written using Pig. Programmers can focus more on writing the core analytics logic rather than getting worried about so many mappers/reducers for each intermediate sub-task. Review collected by and hosted on G2.com.