Sparklyr On HDInsight

Kevin Feasel

2016-11-11

Cloud, Hadoop, R

Ali Zaidi has a walkthrough on using sparklyr on HDInsight:

The majority of Spark is written in Scala (~80% of Spark core), which is a functional programming language. Functional programming languages emphasize functional purity (the output only depends on the inputs) and strive to avoid side-effects. One important component of most functional programming languages is their lazy evaluation. While it might seem odd that we would appreciate laziness from our computing tools, lazy evaluation is an effective way of ensuring computations are evaluated in the most efficient manner possible.

Lazy evaluation allows Spark SQL to highly optimize the queries. When a user submits a query to Spark SQL, Spark composes the components of the SQL query into a logical plan. The logical plan is basically a recipe Spark SQL creates in order to evaluate the desired query. Spark SQL then submits the logical plan to its highly optimized engine called Catalyst, which optimizes this plan into a physical plan of action that is executed inside Spark computation engine (a series of coordinating JVMs).

Read on for more description and code.

Related Posts

Polar Charts In Power BI With R

Leila Etaati shows how to build a polar chart in Power BI using an R component: I just add a layer to the above furmula “coord_polar()” this function also has been used for creating pie charts. it gets the “theta” variable, in below example I put theta=y axis, so we have below charts Normally I […]

Read More

Long-Term Storage In Kafka

Jay Kreps shows us that you can use Kafka as a primary data store: The short answer is that it’s not insane, people do this all the time, and Kafka was actually designed for this type of usage. But first, why might you want to do this? There are actually a number of use cases, […]

Read More

Categories

November 2016
MTWTFSS
« Oct Dec »
 123456
78910111213
14151617181920
21222324252627
282930