tbl_cache

Force a Spark table with name <code>name</code> to be loaded into memory.
Operations on cached tables should normally (although not always)
be more performant than the same operation performed on an uncached
table.

R interface to Apache Spark, a fast and general
engine for big data processing, see <https://spark.apache.org/>. This
package supports connecting to local and remote Apache Spark clusters,
provides a 'dplyr' compatible back-end, and provides an interface to
Spark's built-in machine learning algorithms.

Edgar Ruiz

sparklyr

R Interface to Apache Spark

Javier Luraschi

Kevin Kuo

Kevin Ushey

JJ Allaire

Samuel Macedo

Hossein Falaki

Lu Wang

Andy Zhang

Yitao Li

Jozef Hajnala

Maciej Szymkiewicz

Wil Davis

 RStudio

 The Apache Software Foundation

tbl_cache function

<dl><dt>sc</dt>
<dd>A <code>spark_connection</code>.</dd>
<dt>name</dt>
<dd>The table name.</dd>
<dt>force</dt>
<dd>Force the data to be loaded into memory? This is accomplished
by calling the <code>count</code> API on the associated Spark DataFrame.</dd></dl>

Arguments

Cache a Spark Table — tbl_cache

<dl>

<dt>sc</dt>
<dd>A <code>spark_connection</code>.</dd>


<dt>name</dt>
<dd>The table name.</dd>


<dt>force</dt>
<dd>Force the data to be loaded into memory? This is accomplished
by calling the <code>count</code> API on the associated Spark DataFrame.</dd>

</dl>

Cache a Spark Table

tbl_cache: Cache a Spark Table

Description

Usage

Arguments