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Get the Report →How to load SAS xpt data into Elasticsearch via Logstash
Introducing a simple method to load SAS xpt data using the ETL module Logstash of the full-text search service Elasticsearch and the CData JDBC driver.
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 xpt to load data from SAS xpt into Elasticsearch via Logstash.
Using CData JDBC Driver for SAS xpt with Elasticsearch Logstash
- Install the CData JDBC Driver for SAS xpt on the machine where Logstash is running.
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The JDBC Driver will be installed at the following path (the year part, e.g. 20XX, will vary depending on the product version you are using). You will use this path later. Place this .jar file (and the .lic file if it's a licensed version) in Logstash.
C:\Program Files\CData\CData JDBC Driver for SASXpt 20XX\lib\cdata.jdbc.sasxpt.jar
- Next, install the JDBC Input Plugin, which connects Logstash to the CData JDBC driver. The JDBC Plugin comes by default with the latest version of Logstash, but depending on the version, you may need to add it.
https://www.elastic.co/guide/en/logstash/5.4/plugins-inputs-jdbc.html - Move the CData JDBC Driver’s .jar file and .lic file to Logstash's "/logstash-core/lib/jars/".
Sending SAS xpt data to Elasticsearch with Logstash
Now, let's create a configuration file for Logstash to transfer SAS xpt data to Elasticsearch.
- Write the process to retrieve SAS xpt data in the logstash.conf file, which defines data processing in Logstash. The input will be JDBC, and the output will be Elasticsearch. The data loading job is set to run at 30-second intervals.
- Set the CData JDBC Driver's .jar file as the JDBC driver library, configure the class name, and set the connection properties to SAS xpt in the form of a JDBC URL. The JDBC URL allows detailed configuration, so please refer to the product documentation for more specifics.
- URI: Set this to the folder within your bucket that you would like to connect to.
- AWSAccessKey: Set this to your AWS account access key.
- AWSSecretKey: Set this to your AWS account secret key.
- TemporaryLocalFolder: Set this to the path, or URI, to the folder that is used to temporarily download SASXpt file(s).
- URI: Set this to the name of the file system and the name of the folder which contacts your SASXpt files.
- AzureAccount: Set this to the name of the Azure Data Lake storage account.
- AzureAccessKey: Set this to our Azure DataLakeStore Gen 2 storage account access key.
- TemporaryLocalFolder: Set this to the path, or URI, to the folder that is used to temporarily download SASXpt file(s).
Connecting to Local SASXpt Files
You can connect to local SASXpt file by setting the URI to a folder containing SASXpt files.
Connecting to S3 data source
You can connect to Amazon S3 source to read SASXpt files. Set the following properties to connect:
Connecting to Azure Data Lake Storage Gen2
You can connect to ADLS Gen2 to read SASXpt files. Set the following properties to connect:
Executing data movement with Logstash
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 xpt data has been loaded into Elasticsearch.
For example, let's view the data transferred to Elasticsearch in Kibana.
GET sasxpt_table/_search { "query": { "match_all": {} } }
We have confirmed that the data is stored in Elasticsearch.
By using the CData JDBC Driver for SAS xpt with Logstash, it functions as a SAS xpt connector, making it easy to load data into Elasticsearch. Please try the 30-day free trial.