If you have an Amazon AWS Marketplace account, you can install Guavus SQLstream as an Amazon Marketplace AMI.
Amazon Machine Images run as virtual machines in the cloud. For more information, see http://docs.aws.amazon.com/AWSEC2/latest/UserGuide/AMIs.html.
The cost of running this AMI includes an element for the underlying EC2, and a corresponding element for the SQLstream license (which is a multiple of the EC2 cost, depending on the size of the EC2 cpu). If you are trialling SQLstream, you are advised to use the Trial AMI which has no license cost included. See Installing the SQLstream AMI.
To use the Guavus SQLstream AMI, it is helpful, but not mandatory, to have experience with Amazon EC2. If you haven’t worked with EC2 before, you will need to both create an Amazon Web Services account and generate a public/private keypair for EC2.
Amazon EC2 uses public/private key crytography to secure login data. To log into an instance on EC2, you will need a public/private keypair. If you have used AWS in the past, you likely have one of these. They can also be created through the AWS site. See http://docs.aws.amazon.com/AWSEC2/latest/UserGuide/ec2-key-pairs.html for more details.
Open the AWS Marketplace home page at https://aws.amazon.com/marketplace/
Enter Guavus SQLstream in the search box at the top of the page.
On the page that opens, click Guavus SQLstream. The page that opens describes Guavus SQLstream and lets you select the region in which you will run the Guavus SQLstream AMI. Choose your region and click Continue.
The page that opens lets you choose an instance type on which the AMI will run. An instance type describes the memory and processors allotted to the image.
By default, the Marketplace Guavus SQLstream AMI runs on an r3.xlarge instance type. Instance types determine how well Guavus SQLstream will perform, but also how much your AMI will cost to run.
To run the Guavus SQLstream AMI, you should select an image type of at least m3.large. We recommend this minimal requirement for demonstration purposes. For production use, you should choose an image type of m3.xlarge or higher. The key here is the number of virtual CPUs available. m3.large provides two CPUs, which is minimal to run s-Server and a data generator in order to run the Mochi demo. You can leave the rest of the settings at their defaults.
Click Launch with 1-click. A page opens with a confirmation message.
Click the EC2 Console link.
In the list of instances, find the instance of Guavus SQLstream.
To the right, you will see a column labeled Public DNS Address. This will be something similar to ec2-54-193-200-69.us-west-1.compute.amazonaws.com.
Select and copy this address and paste it into a browser address bar. The Guavus SQLstream AMI launch page opens.
There is an indicator on the AMI home page at the bottom of the Welcome! section right before the Demonstration section, that indicates the status of s-Server. Once s-Server is connected, it will say “Server is listening on port 5570”. This indicator will not display a “listening” message until installation completes.
From the Guavus SQLstream AMI launch page, you can do the following:
The Mochi demonstration application simulates clusters of failed logins at a bank, either by phone or web, as well as withdrawals or debits using the same customer id number. See the topic Running the Mochi Demo for more details.
To run the Mochi demo, click the “Start Mochi Demo” link. Like the installation of s-Server, this process takes some time to initiate. We recommend waiting 5 minutes to allow the Mochi demo to start. Next, click the “View Mochi Demo” link. This will open a new tab or window in your browser pointing to the dashboard list. If it fails, it probably means you didn’t wait long enough. Close the window, wait a little longer, and try again.
When you’re done with the demo, you can either use the “Stop Mochi Demo” link to shut it down cleanly, or just terminate the EC2 instance if you’re done using it. If you are going to move on to use StreamLab, you need to stop the Mochi demo cleanly.
StreamLab is a web application development environment that automatically generates streaming SQL. StreamLab lets you set up projects where you can parse incoming streaming data, generate real time analytics for it, visualize it, so that you can take action on it. See The StreamLab Guide for more details.
The Launch page links to a video tutorial that walks you through using Stream
SQLstream provides sample data to use with StreamLab. This is a continually-updating file in JSON format. For more information on using StreamLab with bus data, see the topic Using StreamLab to Build a Streaming Application in the Building Applications with Guavus SQLstream guide.
To run StreamLab, click the Try StreamLab link.
You can download and install SQLstream s-Studio. Once you do, you can configure s-Studio to connect with your AMI Guavus SQLstream instance by taking the following steps:
Copy the JDBC address from the top of the AMI launch page.
Right-click First SQLstream Server.
Paste the JDBC address into the URL field and click OK.
Right-click First SQLstream Server again and select Connect.
Studio should connect to s-Server and display a list of schemas, data sources, plugins, and so on.
When you’re done using the instance, you should stop it, either from the EC2 Management Console or from the command line.