Amazon Redshift User Manual

Viewing Events Using AWS SDK for Java
The following example lists the events for a specified cluster and specified event source type.The example
shows how to use pagination.
For step-by-step instructions to run the following example, see Running Java Examples for Amazon
Redshift Using Eclipse (p. 118).You need to update the code and specify a cluster identifier and event
source type.
import java.io.IOException;
import java.util.Date;
import com.amazonaws.auth.AWSCredentials;
import com.amazonaws.auth.PropertiesCredentials;
import com.amazonaws.services.redshift.AmazonRedshiftClient;
import com.amazonaws.services.redshift.model.*;
public class ListEvents {
public static AmazonRedshiftClient client;
public static String clusterIdentifier = "***provide cluster identifier***";
public static String eventSourceType = "***provide source type***"; // e.g.
cluster-snapshot
public static void main(String[] args) throws IOException {
AWSCredentials credentials = new PropertiesCredentials(
ListEvents.class
.getResourceAsStream("AwsCredentials.properties"));
client = new AmazonRedshiftClient(credentials);
try {
listEvents();
} catch (Exception e) {
System.err.println("Operation failed: " + e.getMessage());
}
}
private static void listEvents() {
long oneWeeksAgoMilli = (new Date()).getTime() - (7L*24L*60L*60L*1000L);
Date oneWeekAgo = new Date();
oneWeekAgo.setTime(oneWeeksAgoMilli);
String marker = null;
do {
DescribeEventsRequest request = new DescribeEventsRequest()
.withSourceIdentifier(clusterIdentifier)
.withSourceType(eventSourceType)
.withStartTime(oneWeekAgo)
.withMaxRecords(20);
DescribeEventsResult result = client.describeEvents(request);
marker = result.getMarker();
for (Event event : result.getEvents()) {
printEvent(event);
API Version 2012-12-01
65
Amazon Redshift Management Guide
Viewing Events Using AWS SDK for Java

Amazon Redshift Specifications

General

Provider	Amazon Web Services (AWS)
Query Language	SQL
Data Storage	Columnar storage
Security	Encryption at rest and in transit, VPC, IAM
Backup	Automated and manual snapshots
Deployment	Cloud-based
Type	Cloud-based data warehouse service
Primary Use	Data warehousing, analytics
Integration	Integrates with AWS services, BI tools, and ETL tools
Pricing Model	On-demand and reserved instance pricing
Data Compression	Columnar storage with data compression
Performance Optimization	Query optimization