Dust is a JavaScript templating engine that allows templates to be compiled to JavaScript for fast rendering on both the server and client side. It supports hierarchical data structures through context and path notation. Templates can reference data within the current context or higher contexts. Explicit context and parameters can also be passed to templates. Dust works anywhere JavaScript works and has no other dependencies.
This is a follow-up to my PHP://memory and streams for scaling talk I gave at PHP|Tek12 in Chicago. Presented to the local Baltimore PHP User Group on 2012-06-20
MongoDB presentation for NYC Python's June meetup. Brief discussion on non-relational databases in general followed by an example of using MongoDB as a blog's backend
This is a follow-up to my PHP://memory and streams for scaling talk I gave at PHP|Tek12 in Chicago. Presented to the local Baltimore PHP User Group on 2012-06-20
MongoDB presentation for NYC Python's June meetup. Brief discussion on non-relational databases in general followed by an example of using MongoDB as a blog's backend
In this presentation, you will see simple ways of quickly deploying MySQL and start exploring the potential of SQL databases.
You will see how to deploy locally, using docker and some potential of the SQL language to extract not only data, but useful information from the database.
This presentation is recommended for begineers.
Agenda:
MongoDB Overview/History
Workshop
1. How to perform operations to MongoDB – Workshop
2. Using MongoDB in your Java application
Advance usage of MongoDB
1. Performance measurement comparison – real life use cases
3. Doing Cluster setup
4. Cons of MongoDB with other document oriented DB
5. Map-reduce/ Aggregation overview
Workshop prerequisite
1. All participants must bring their laptops.
2. https://github.com/geek007/mongdb-examples
3. Software prerequisite
a. Java version 1.6+
b. Your favorite IDE, Preferred http://www.jetbrains.com/idea/download/
c. MongoDB server version – 2.6.3 (http://www.mongodb.org/downloads - 64 bit version)
d. Participants can install MongoDB client – http://robomongo.org/
About Speaker:
Akbar Gadhiya is working with Ishi Systems as Programmer Analyst. Previously he worked with PMC, Baroda and HCL Technologies.
What happens when you start transitioning from a monolithic PHP app to Go services running on AWS Lambda? Good things! I'd like to share the problems encountered, decisions made and lessons learned along the way.
Backend Development with AWS & Flask
Daniel Laufer on November 24, 2021
Learn about backend development through using Flask, a Python web framework, and Amazon Web Services (AWS), the leading cloud service provider in the world!
Java Developers, make the database work for you (NLJUG JFall 2010)Lucas Jellema
The general consensus among Java developers has evolved from a dogmatic strive for database independence to a much more pragmatic wish to leverage the power of the database. This session demonstrates some of the (hidden) powers of the database and how these can be utilized from Java applications using either straight JDBC or working through JPA. The Oracle database is used as example: SQL for Aggregation and Analysis, Flashback Queries for historical comparison and trends, Virtual Private Database, complex validation, PL/SQL and collections for bulk data manipulation, view and instead-of triggers for data model morphing, server push of relevant data changes, edition based redefinition for release management.
- overview of role of database in JEE architecture (and a little history on how the database is perceived through the years)
- discussion on the development of database functionality
- demonstration of some powerful database features
- description of how we leveraged these features in our JSF (RichFaces)/JPA (Hibernate) application
- demo of web application based on these features
- discussion on how to approach the database
Slides of our talk at adaptTo 2016, Chetan Mehrotra and myself (https://adapt.to/2016/en/schedule/let_s-run-the-whole-web-on-apache-sling-and-oak-.html).
The code is at https://github.com/bdelacretaz/sling-adaptto-2016 and uses Docker to build a dynamic cluster of Apache Sling instances.
Presentation on some of my recent experiences with Microsoft Azure, Amazon S3, GoGrid and other cloud technologies, especially while developing:
- http://www.runsaturday.com
- http://www.stacka.com
- http://www.clouddotnet.com
I'm presenting this tonight at the London .Net User's group - but thought it would be useful to share more widely!
If you need more info, contact me@slodge.com - please mark your email with No Spam somehow... hopefully it will get through to me.
This webinar (done in December,2007) shows how the new Data Services capability in WSO2's Web Services Application Server can become a key component in your SOA/Data strategy. Using simple screens and a basic knowledge of SQL, any database programmer or administrator can configure and expose Data Services. As well as major databases such as Oracle, DB2 and MySQL, you can also extract data from Excel and CSV files.
Powerful big data processing and storage combined, this presentation walks thru the basics of integrating Apache Spark and Apache Cassandra. Presented by Alex Thompson at the Sydney Cassandra Meetup.
Jump Start with Apache Spark 2.0 on DatabricksAnyscale
Apache Spark 2.x has laid the foundation for many new features and functionality. Its main three themes—easier, faster, and smarter—are pervasive in its unified and simplified high-level APIs for Structured data.
In this introductory part lecture and part hands-on workshop you’ll learn how to apply some of these new APIs using Databricks Community Edition. In particular, we will cover the following areas:
Apache Spark Fundamentals & Concepts
What’s new in Spark 2.x
SparkSessions vs SparkContexts
Datasets/Dataframes and Spark SQL
Introduction to Structured Streaming concepts and APIs
In this presentation, you will see simple ways of quickly deploying MySQL and start exploring the potential of SQL databases.
You will see how to deploy locally, using docker and some potential of the SQL language to extract not only data, but useful information from the database.
This presentation is recommended for begineers.
Agenda:
MongoDB Overview/History
Workshop
1. How to perform operations to MongoDB – Workshop
2. Using MongoDB in your Java application
Advance usage of MongoDB
1. Performance measurement comparison – real life use cases
3. Doing Cluster setup
4. Cons of MongoDB with other document oriented DB
5. Map-reduce/ Aggregation overview
Workshop prerequisite
1. All participants must bring their laptops.
2. https://github.com/geek007/mongdb-examples
3. Software prerequisite
a. Java version 1.6+
b. Your favorite IDE, Preferred http://www.jetbrains.com/idea/download/
c. MongoDB server version – 2.6.3 (http://www.mongodb.org/downloads - 64 bit version)
d. Participants can install MongoDB client – http://robomongo.org/
About Speaker:
Akbar Gadhiya is working with Ishi Systems as Programmer Analyst. Previously he worked with PMC, Baroda and HCL Technologies.
What happens when you start transitioning from a monolithic PHP app to Go services running on AWS Lambda? Good things! I'd like to share the problems encountered, decisions made and lessons learned along the way.
Backend Development with AWS & Flask
Daniel Laufer on November 24, 2021
Learn about backend development through using Flask, a Python web framework, and Amazon Web Services (AWS), the leading cloud service provider in the world!
Java Developers, make the database work for you (NLJUG JFall 2010)Lucas Jellema
The general consensus among Java developers has evolved from a dogmatic strive for database independence to a much more pragmatic wish to leverage the power of the database. This session demonstrates some of the (hidden) powers of the database and how these can be utilized from Java applications using either straight JDBC or working through JPA. The Oracle database is used as example: SQL for Aggregation and Analysis, Flashback Queries for historical comparison and trends, Virtual Private Database, complex validation, PL/SQL and collections for bulk data manipulation, view and instead-of triggers for data model morphing, server push of relevant data changes, edition based redefinition for release management.
- overview of role of database in JEE architecture (and a little history on how the database is perceived through the years)
- discussion on the development of database functionality
- demonstration of some powerful database features
- description of how we leveraged these features in our JSF (RichFaces)/JPA (Hibernate) application
- demo of web application based on these features
- discussion on how to approach the database
Slides of our talk at adaptTo 2016, Chetan Mehrotra and myself (https://adapt.to/2016/en/schedule/let_s-run-the-whole-web-on-apache-sling-and-oak-.html).
The code is at https://github.com/bdelacretaz/sling-adaptto-2016 and uses Docker to build a dynamic cluster of Apache Sling instances.
Presentation on some of my recent experiences with Microsoft Azure, Amazon S3, GoGrid and other cloud technologies, especially while developing:
- http://www.runsaturday.com
- http://www.stacka.com
- http://www.clouddotnet.com
I'm presenting this tonight at the London .Net User's group - but thought it would be useful to share more widely!
If you need more info, contact me@slodge.com - please mark your email with No Spam somehow... hopefully it will get through to me.
This webinar (done in December,2007) shows how the new Data Services capability in WSO2's Web Services Application Server can become a key component in your SOA/Data strategy. Using simple screens and a basic knowledge of SQL, any database programmer or administrator can configure and expose Data Services. As well as major databases such as Oracle, DB2 and MySQL, you can also extract data from Excel and CSV files.
Powerful big data processing and storage combined, this presentation walks thru the basics of integrating Apache Spark and Apache Cassandra. Presented by Alex Thompson at the Sydney Cassandra Meetup.
Jump Start with Apache Spark 2.0 on DatabricksAnyscale
Apache Spark 2.x has laid the foundation for many new features and functionality. Its main three themes—easier, faster, and smarter—are pervasive in its unified and simplified high-level APIs for Structured data.
In this introductory part lecture and part hands-on workshop you’ll learn how to apply some of these new APIs using Databricks Community Edition. In particular, we will cover the following areas:
Apache Spark Fundamentals & Concepts
What’s new in Spark 2.x
SparkSessions vs SparkContexts
Datasets/Dataframes and Spark SQL
Introduction to Structured Streaming concepts and APIs
3. ▪ Dust is a Javascript templating
engine
▪ Designed to run asynchronously
on both the server and the browser
▪ Not truly Logic Less
▪ Dust works where Javascript
works
4. Advantages
–Template is compiled to Javascript
–Available on client side, so faster rendering and less network
load
–Dust can precompile your templates , or dynamically load
them
–Dust works where Javascript works, No other dependencies
5. Example
// Template
Hello {name}! You have {count} new messages.
// Data
{
"name": "Mick",
"count": 30
}
// Result
Hello Mick! You Have 30 new messages.
6. Section and context
–A simple key reference will look first in the current context
and, if not found, search all higher levels up to the root looking
for the name
–It will not search downward
–{#A}{anotherName}{/A} outputs "rootName"
7. Paths
–If we want to work only with the data within a specific context,
we can use dotted notation (called paths) to define the context
–{A.B.name} will output "Bob"
–Path notation allows you to reference a path outside a current
context
8. Paths
// Template
{#A.B}
Name in B = {name}, Name in A =
{A.name}
{/A.B}
// Data
{
"name": "root",
"anotherName": "root2",
"A":{
"name":"Albert",
"B":{
"name":"Bob"
}
}
}
//Result
Name in B = Bob, name in A = Albert