Answer:A UDF has input and output. Here is the different ways you can specify the output format of a Python UDF through use of the outputSchema decorator.
Answer:Pig does not have a dedicated metadata database. Hive makes use of the exact variation of dedicated SQL-DDL language by defining tables beforehand. 14. It supports Avro file format.
Answer:It is used for semi structured data. ,Hive is query engine,HBase is a data storage particularly for unstructured data.
Answer:Apache Pig is a tool for analytics which is used to analyze data stored in HDFS. Apache Sqoop is a tool to importing structured data from RDBMS to HDFS or exporting data from HDFS to RDBMS.
Answer:Pig is a scripting language,SQL like query language,It is a compiled language
Answer:Pig Hadoop Component is generally used by Researchers and Programmers. Hive Hadoop Component is mainly used by data analysts.
Answer:Apache Pig is a high-level,Apache Hive is a data warehouse software project,Open-source software framework
Answer:For readability GROUP is used Cogroup used as a statements
Answer:It contains easy programming
Answer:The development time is Decrease….
Answer:HBASE will not replace Map Reduce. It is scalable distributed database….
Answer:Where XXX is the number of reducer.
Answer:Pig Latin is not a language but its a language game that all use to speak in code
Answer:User can perform all the data manipulation operations in Hadoop using Apache Pig
Answer:Pig programming language is used for obtaining and manipulating data perhaps doing otherwise with UDFs…..
Answer:The FOREACH operator is used to generate specified data transformations based on the column data.
Answer:Joining skewed data using apache Pig skewed join.In a distributed processing environment Data skew is a serious problem,and occurs when the data is not evenly divided among the key tuples from the map phase.
Answer:Pig Latin consist of pig to analyze the data from Hadoop
Answer:In 2006 Pig was developed by Yahoo Research for particular way of creating and executing MapReduce jobs on very large data sets.