Can a custom data type be created and implemented in MapReduce?

Since a data type implementing WritableComparable can be used as data type for key or value fields in mapreduce programs, Lets define a custom data type which can used for both key and value fields.

Can a custom data type be created and implemented in MapReduce?

Since a data type implementing WritableComparable can be used as data type for key or value fields in mapreduce programs, Lets define a custom data type which can used for both key and value fields.

What are the data types in MapReduce?

Define Writable data types in Hadoop MapReduce.

  • Integer –> IntWritable: It is the Hadoop variant of Integer.
  • Float –> FloatWritable: Hadoop variant of Float used to pass floating point numbers as key or value.
  • Long –> LongWritable: Hadoop variant of Long data type to store long values.

What is custom writable in Hadoop?

Writable is an interface in Hadoop. Writable in Hadoop acts as a wrapper class to almost all the primitive data type of Java. That is how int of java has become IntWritable in Hadoop and String of Java has become Text in Hadoop. Writables are used for creating serialized data types in Hadoop.

How do you implement a custom writable in Hadoop io?

Implementing Writable requires implementing two methods, readFields(DataInput in) and write(DataOutput out) . Writables that are used as keys in MapReduce jobs must also implement Comparable (or simply WritableComparable).

What should be done to implement a custom hadoop key and value?

If you want to use same class for your key and value, Then you need to write only one custom class which implements WritableComparable Interface. A class which implements WritableComparable interface can be used for Key and Value. That means your new custom class will be Writable and Comparable also.

Why key type should be both writable and comparable in MapReduce programs?

1)WritableComparables can be compared to each other, typically via Comparators. Any type which is to be used as a key in the Hadoop Map-Reduce framework should implement this interface. 2) Any type which is to be used as a value in the Hadoop Map-Reduce framework should implement the Writable interface.

What are Hadoop data types?

Data types that are supported by Big SQL for Hadoop and HBase tables

Data type supported in CREATE TABLE (HADOOP/HBASE) Big SQL data type
DECIMAL(p,s) DECIMAL
DOUBLE 64-bit IEEE float
FLOAT 64-bit IEEE float
INTEGER 32-bit signed integer

What are the different types of Hadoop data?

Here are the Hive data types that the Hadoop engine supports.

  • Numeric data. BIGINT. FLOAT. BOOLEAN. INT. DECIMAL. SMALLINT. DOUBLE. TINYINT.
  • String data. BINARY. STRING. CHARn. VARCHARn.
  • Date and time data. DATE. TIMESTAMP. INTERVAL.
  • Complex data. ARRAY. STRUCT. MAP.

What is writable interface?

Interface Writable A serializable object which implements a simple, efficient, serialization protocol, based on DataInput and DataOutput . Any key or value type in the Hadoop Map-Reduce framework implements this interface.

What are object writable in big data?

Class ObjectWritable. A polymorphic Writable that writes an instance with it’s class name. Handles arrays, strings and primitive types without a Writable wrapper.

How do I optimize MapReduce?

6 Best MapReduce Job Optimization Techniques

  1. Proper configuration of your cluster.
  2. LZO compression usage.
  3. Proper tuning of the number of MapReduce tasks.
  4. Combiner between Mapper and Reducer.
  5. Usage of most appropriate and compact writable type for data.
  6. Reusage of Writables.

What is input format in hadoop?

Hadoop InputFormat describes the input-specification for execution of the Map-Reduce job. InputFormat describes how to split up and read input files. In MapReduce job execution, InputFormat is the first step. It is also responsible for creating the input splits and dividing them into records.