Pig vs Presto vs Apache Spark



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What is Pig?

Pig is a dataflow programming environment for processing very large files. Pig's language is called Pig Latin. A Pig Latin program consists of a directed acyclic graph where each node represents an operation that transforms data. Operations are of two flavors: (1) relational-algebra style operations such as join, filter, project; (2) functional-programming style operators such as map, reduce.

What is Presto?

Presto is an open source distributed SQL query engine for running interactive analytic queries against data sources of all sizes ranging from gigabytes to petabytes.

What is Apache Spark?

Spark is a fast and general processing engine compatible with Hadoop data. It can run in Hadoop clusters through YARN or Spark's standalone mode, and it can process data in HDFS, HBase, Cassandra, Hive, and any Hadoop InputFormat. It is designed to perform both batch processing (similar to MapReduce) and new workloads like streaming, interactive queries, and machine learning.

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Why do developers choose Pig?
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What are the cons of using Pig?
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      What are some alternatives to Pig, Presto, and Apache Spark?
      Capybara helps you test web applications by simulating how a real user would interact with your app. It is agnostic about the driver running your tests and comes with Rack::Test and Selenium support built in. WebKit is supported through an external gem.
      Amazon Athena
      Amazon Athena is an interactive query service that makes it easy to analyze data in Amazon S3 using standard SQL. Athena is serverless, so there is no infrastructure to manage, and you pay only for the queries that you run.
      Apache Flink
      Apache Flink is an open source system for fast and versatile data analytics in clusters. Flink supports batch and streaming analytics, in one system. Analytical programs can be written in concise and elegant APIs in Java and Scala.
      Druid is a distributed, column-oriented, real-time analytics data store that is commonly used to power exploratory dashboards in multi-tenant environments. Druid excels as a data warehousing solution for fast aggregate queries on petabyte sized data sets. Druid supports a variety of flexible filters, exact calculations, approximate algorithms, and other useful calculations.
      Apache Hive
      Hive facilitates reading, writing, and managing large datasets residing in distributed storage using SQL. Structure can be projected onto data already in storage.
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      What tools integrate with Pig?
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      What tools integrate with Apache Spark?
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          How developers use Pig, Presto, and Apache Spark
          Avatar of Wei Chen
          Wei Chen uses Apache SparkApache Spark

          Spark is good at parallel data processing management. We wrote a neat program to handle the TBs data we get everyday.

          Avatar of Ralic Lo
          Ralic Lo uses Apache SparkApache Spark

          Used Spark Dataframe API on Spark-R for big data analysis.

          Avatar of Kalibrr
          Kalibrr uses Apache SparkApache Spark

          We use Apache Spark in computing our recommendations.

          Avatar of BrainFinance
          BrainFinance uses Apache SparkApache Spark

          As a part of big data machine learning stack (SMACK).

          Avatar of Dotmetrics
          Dotmetrics uses Apache SparkApache Spark

          Big data analytics and nightly transformation jobs.

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