Data Science in Spark with sparklyr - GitHub
[Pages:2]Data Science in Spark with Sparklyr : : CHEAT SHEET
Intro
sparklyr is an R interface for Apache SparkTM,
it provides a complete dplyr backend and the option to query directly using Spark SQL statement. With sparklyr, you can orchestrate distributed machine learning using either Spark's MLlib or H2O Sparkling Water.
Starting with version 1.044, RStudio Desktop, Server and Pro include integrated support for the sparklyr package. You can create and manage connections to Spark clusters and local Spark instances from inside the IDE.
RStudio Integrates with sparklyr
Open connection log
Disconnect
Open the Spark UI
Spark & Hive Tables
Preview 1K rows
Cluster Deployment
MANAGED CLUSTER
Worker Nodes
Cluster Manager Driver Node
fd
YARN
fd
or
Mesos
fd
STAND ALONE CLUSTER Worker Nodes
Driver Node
fd fd
fd
Data Science Toolchain with Spark + sparklyr
Import
? Export an R DataFrame
? Read a file ? Read existing
Hive table
Tidy ? dplyr verb ? Direct Spark
SQL (DBI) ? SDF function
(Scala API)
R for Data Science, Grolemund & Wickham
Understand
Transform Transformer function
Visualize Collect data into R for plotting
Wrangle
Model ? Spark MLlib ? H2O Extension
Communicate
? Collect data into R
? Share plots, documents, and apps
Using sparklyr
A brief example of a data analysis using Apache Spark, R and sparklyr in local mode
library(sparklyr); library(dplyr); library(ggplot2);
library(tidyr); set.seed(100)
Install Spark locally
Getting Started
LOCAL MODE (No cluster required)
ON A YARN MANAGED CLUSTER
spark_install("2.0.1") Connect to local version sc ................
................
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