What is the use of RecordReader in Hadoop?
What is the use of RecordReader in Hadoop?
RecordReader , typically, converts the byte-oriented view of the input, provided by the InputSplit , and presents a record-oriented view for the Mapper and Reducer tasks for processing. It thus assumes the responsibility of processing record boundaries and presenting the tasks with keys and values.
What is role of custom input format in MapReduce?
Role of InputFormat Validate the input configuration for the job (checking that the data is there). 2. Split the input blocks and files into logical chunks of type InputSplit, each of which is assigned to a map task for processing.
What is the role of RecordReader in MapReduce?
In MapReduce, RecordReader load data from its source and it converts the data into key-value pairs suitable for reading by the mapper. RecordReader communicates with the inputsplit until it does not read the complete file.
What is MapReduce in Hadoop with example?
MapReduce programming paradigm allows you to scale unstructured data across hundreds or thousands of commodity servers in an Apache Hadoop cluster. It has two main components or phases, the map phase and the reduce phase. The input data is fed to the mapper phase to map the data.
What is Record writer?
RecordWriter is a class, whose implementation is provided by the OutputFormat, collects the output key-value pairs from the Reducer and writes it into the output file. The way these output key-value pairs are written in output files by RecordWriter is determined by the OutputFormat.
Which input format is mostly used in MapReduce?
Initially, the data for a MapReduce task is stored in input files, and input files typically reside in HDFS. Although these files format is arbitrary, line-based log files and binary format can be used.
What are the most common input format in Hadoop?
What are the most common InputFormats in Hadoop?
- Most common InputFormat are:
- FileInputFormat- It is the base class for all file-based InputFormat.
- TextInputFormat- It is the default InputFormat of MapReduce.
- KeyValueTextInputFormat- It is similar to TextInputFormat.
How many daemon processes run on a Hadoop system?
five separate daemons
How many Daemon processes run on a Hadoop system? Hadoop is comprised of five separate daemons. Each of these daemon run in its own JVM. Following 3 Daemons run on Master nodes NameNode – This daemon stores and maintains the metadata for HDFS.
How many mappers would be running in an application?
Usually, 1 to 1.5 cores of processor should be given to each mapper. So for a 15 core processor, 10 mappers can run.
What is custom partitioner in Hadoop?
Custom Partitioners are written in a MapReduce job whenever there is a requirement to divide the data set more than two times. Custom Partitioner is a process that allows you to store the results in different reducers, based on the user condition.