Data Mining Demo: Modelling and forecasting with R and EXASOL

In the following you will find a simple data mining demo that shows modelling and forecasting in the connection of R and Exasol. If you have not performed the installation and configuration of the necessary components yet, you can find an instruction here.

The iris data are now transferred to the Exasol. At first use, a database schema and an empty table are created. Afterwards, the iris data are written into the table. Once the data are uploaded they can be used time and again.
In the first step of the analysis a decision tree is created locally. Based on this tree a forecast is done.
The same procedure as above now in the Exasol. The exa.script function creates an R script on the Exasol server. The function call runs the script on the Exasol clusters. This means that the analysis no longer takes place on the local R but on the R instances in the Exasol cluster. Packages which are used on the R instances on the Exasol need to be installed there. Have a look at this blog entry for more information.

The model built in the Exasol cluster will be stored in Redis, a key-value database. With Redis you can distribute models, functions and other R objects in the cluster and load them from the cluster.

The tree model can be used for forecasting in a separate step on the Exasol. The first part is mostly identical with the above function.

In the following you will find a simple data mining demo that shows modelling and forecasting in the connection of R and Exasol. If you have not performed the installation and configuration of the necessary components yet, you can find an instruction here.

The iris data are now transferred to the Exasol. At first use, a database schema and an empty table are created. Afterwards, the iris data are written into the table. Once the data are uploaded they can be used time and again.

In the first step of the analysis a decision tree is created locally. Based on this tree a forecast is done.

The same procedure as above now in the Exasol. The exa.script function creates an R script on the Exasol server. The function call runs the script on the Exasol clusters. This means that the analysis no longer takes place on the local R but on the R instances in the Exasol cluster. Packages which are used on the R instances on the Exasol need to be installed there. Have a look at this blog entry for more information.

The model built in the Exasol cluster will be stored in Redis, a key-value database. With Redis you can distribute models, functions and other R objects in the cluster and load them from the cluster.

The tree model can be used for forecasting in a separate step on the Exasol. The first part is mostly identical with the above function.

eoda GmbH - Posted on 20.06.2016

Als Data Science Spezialisten sind wir Ihr Ansprechpartner im Umfeld von Big Data, Machine Learning und Künstlicher Intelligenz. Wir unterstützen Sie ganzheitlich – von der Identifikation des richtigen Anwendungsfalls über die Datenanalyse und Interpretation der Ergebnisse bis hin zur Implementierung der entwickelten Lösung in Ihr Produktivsystem.

Subscribe!