Data Type Mapping Between R and Spark | Learn R and Spark

Keeping you updated with latest technology trends, Join DataFlair on Telegram

1. Objective

Today, in this Spark tutorial, we will learn the Data type mapping between R and Spark. Before, them we will also learn a brief introduction to SparkR

So, let’s start Data Type Mapping Between R and Spark.

Data type mapping between R and Spark

Data type mapping between R and Spark

2. What is SparkR?

Apache Spark 1.4 releases SparkR. One of the major components of SparkR is SparkR DataFrame. Basically, it is nothing but fundamental data structure for data processing in R. Moreover, DataFrames concept extends to other languages with libraries, for example, Pandas etc.
In addition, R offers several software facilities for data manipulation, calculation, and graphical display. Therefore, the key concept behind SparkR was to explore different techniques to integrate the usability of R with the scalability of Spark. Basically, it is the R package. Also gives light-weight frontend to use Apache Spark from R.
Moreover, Using SparkR is beneficial in the following ways:

a. SparkR Data Sources API

Basically, API SparkR can read in data from a variety of sources. It is possible by tying into Spark SQL’s data sources. For example, Hive tables, JSON files, Parquet files etc.

b. SparkR Data Frame Optimizations

Moreover, it inherits all the optimizations made to the computation engine. That is in terms of code generation, memory management.

c. SparkR Scalability to Many Cores and Machines

Although, those operations which execute on SparkR DataFrames get distributed across all the cores and machines over theSpark cluster. Therefore, SparkR DataFrames can run on terabytes of data and clusters with thousands of machines.

3. Data type mapping between R and Spark

R Spark
byte byte
integer integer
float float
double double
numeric double
character string
string string
binary binary
raw binary
logical boolean
POSIXct timestamp
POSIXlt timestamp
Date date
array array
list array
env map

So, this was all in Spark and R data type mapping. Hope you like our explanation.

4. Conclusion

Hence, we have learned about Data type mapping between R and Spark. Also, learned about SparkR. However, if any query occurs, feel free to ask in the comment section. I assure you that we will get back to you.
Best Books for learning Spark.
For reference

Leave a Reply

Your email address will not be published. Required fields are marked *

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.