How can you optimize Pig scripts to reduce disk I/O? How does Apache Pig handle the network communication between MapReduce tasks generated by Pig?
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what is apache pig
- How do you use the GENERATE clause in Pig?
- What are the advantages and disadvantages of using Pig for feature engineering compared to other tools? How does Apache Pig handle the deployment of Pig scripts as part of larger data applications?
- How can Pig scripts be made more resilient to schema changes? How does Apache Pig handle the integration with distributed key-value stores for data lookup and enrichment during Pig processing?
- Does Pig support data encryption? How does Pig handle authentication and authorization?
- Can Pig scripts be integrated into workflows managed by tools like Apache Airflow or Oozie?
- How do you join elements within bags in Pig?
- How does Apache Pig compare to SQL?
- Are there specialized tools for graph processing with Hadoop? Can Pig be used for machine learning tasks?
- What are the different ways to store data from Pig? How do you filter data in Pig?
- What are some techniques for dealing with data heterogeneity using Pig? How does Apache Pig handle the integration with enterprise security frameworks and authentication/authorization mechanisms to ensure secure data access and processing?
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