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Elasticsearch is a popular distributed full-text search engine. By centrally storing data, you can perform ultra-fast searches, fine-tuning relevance, and powerful analytics with ease. Elasticsearch has a pipeline tool for loading data called "Logstash". You can use CData JDBC Drivers to easily import data from any data source into Elasticsearch for search and analysis.
This article explains how to use the CData JDBC Driver for SAS Data Sets to load data from SAS Data Sets into Elasticsearch via Logstash.
Now, let's create a configuration file for Logstash to transfer SAS Data Sets data to Elasticsearch.
Set the following connection properties to connect to your SAS DataSet files:
While the driver is capable of pulling data from SAS DataSet files hosted on a variety of cloud data stores, INSERT, UPDATE, and DELETE are not supported outside of local files in this driver.
Set the Connection Type to the service hosting your SAS DataSet files. A unique prefix at the beginning of the URI connection property is used to identify the cloud data store and the remainder of the path is a relative path to the desired folder (one table per file) or single file (a single table). For more information, refer to the Getting Started section of the Help documentation.
Now let's run Logstash using the created "logstash.conf" file.
logstash-7.8.0\bin\logstash -f logstash.conf
A log indicating success will appear. This means the SAS Data Sets data has been loaded into Elasticsearch.
For example, let's view the data transferred to Elasticsearch in Kibana.
GET sasdatasets_table/_search
{
"query": {
"match_all": {}
}
}
👁 Querying the SAS Data Sets data loaded into ElasticsearchWe have confirmed that the data is stored in Elasticsearch.
👁 Confirming the SAS Data Sets data loaded into ElasticsearchBy using the CData JDBC Driver for SAS Data Sets with Logstash, it functions as a SAS Data Sets connector, making it easy to load data into Elasticsearch. Please try the 30-day free trial.
Download a free trial of the SAS Data Sets Driver to get started:
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