To get started using SQLstream Blaze, install SQLstream s-Server following the steps in the Installation Guide. s-Server installs with everything you need to view data visualizations, including s-Dashboard and the s-Server WebAgent. The installation guide also describes using the Mochi demo, which uses both of these tools to visualize an alert system for bank login failures. Once you have viewed the Mochi demo, you can install SQLstream StreamLab to start creating your own visualizations based on the Mochi data.
s-Server version 5.2 adds features for reading from and writing data to other systems, transforming data in s-Server, querying data, managing streams, and adding passwords to users. See Summary of 5.2 Features below.
This guide offers an overview of SQLstream s-Server concepts including streams, the system architecture, application models. It also compares streaming SQL with RDMS SQL.
This guide provides instructions on how to install SQLstream s-Server, SQLstream s-Studio, SQLstream client tools, and SQLstream StreamLab.
This guide provides instructions for building a pipeline in s-Server.
This guide describes how to read data into s-Server from the file system, network sockets, Apache Kafka topics, AMQP messages, Amazon Kinesis streams, RDBMS systems, and other sources.
This guide describes how to write data from s-Server into the file system, network sockets, Apache Kafka topics, AMQP messages, Amazon Kinesis streams, RDBMS systems, and other locations
This guide describes how to transform data in s-Server, using SQL, User Defined Transforms and User Defined Functions.
This guide describes how to use StreamLab to parse, analyze, and display s-Server data graphically.
This document explains how to use SQLstream's integrated development environment, s-Studio, to parse, analyze, and output s-Server data.
This document describes how to use s-Dashboard to display s-Server data graphically.
This document explains how to use a customized version of a console based utility to execute SQL in s-Server.
This guide offers comprehensive documentation of SQLstream s-Server streaming SQL, including the particular implementation of CREATE, ALTER, SELECT, and DROP statements.
This guide explains how to configure, maintain, and monitor s-Server once you have installed it.
Defines key terms used for SQLstream s-Server.
You can now write from s-Server to Snowflake warehouses. See the topic Writing to Snowflake Warehouses.
You can now write from s-Server to MongoDB collections. See the topic Writing to MongoDB Collections.
You can now format files as BSON.
s-Server now incorporates machine learning systems such as SystemML and DataRobot. See Using s-Server for Machine Learning with Integrated Apache SystemML and Building a UDX with DataRobot.
You can now use run Kalman filters on streams of sensor data. A Kalman filter is a technique for sharpening the measurements produced by blurry sensors. See Using the Kalman Filter UDX.
Matched Filter UDX. Allows you to evaluate a template against a signal, giving a correlation coefficient for how close the match was at any point within the signal.
A new built-in function, TSDIFF, lets you determine the difference between two timestamp expressions in miliseconds.
s-Server now features offset and hopping windows.
Managing s-Server Objects
ALTER STREAM. ALTER STREAM lets you control data flowing through native streams, allowing you to pause streams temporarily or reset their stream clock. You can pause streams individually, or pause all streams in a schema, using any expression that refers to one or more streams.
ALTER USER. ALTER USER lets you add a password to a user, including the system administrator.