here are some slides for introduction to C++. this slide is merely for basic understanding for C++. this powerpoint is written in Traditional Chinese(TW) and is owned by a group named "Awakening Lion" which I participate in.
here are some slides for introduction to C++. this slide is merely for basic understanding for C++. this powerpoint is written in Traditional Chinese(TW) and is owned by a group named "Awakening Lion" which I participate in.
Big Data for the Rest of Us - OpenWest 2014 - Matt AsayMatt Asay
Everyone wants to launch a Big Data project, but there's still lots of confusion as to how. The key, as this presentation shows, is to minimize the cost of failure and increase iteration, using a strategy based on using well-known open-source tools.
DataStax: Steps to successfully implementing NoSQL in the enterpriseDataStax Academy
NoSQL is the right technology for web, mobile, and IoT applications, but how can you make sure that it's successfully rolled out and implemented in your organization? What are the steps needed for NoSQL to hit the mark and make a difference and what criteria can you use to make the right choice between RDBMS's, NoSQL, and Hadoop?
This sessions covers diagnosing and solving common problems encountered in production, using performance profiling tools. We’ll also give a crash course to basic JVM garbage collection tuning. Attendees will leave with a better understanding of what they should look for when they encounter problems with their in-production Cassandra cluster. This talk is intended for people with a general understanding of Cassandra, but it not required to have experience running it in production.
Cassandra Summit 2014: TitanDB - Scaling Relationship Data and Analysis with ...DataStax Academy
Presenter: Matthias Broecheler, Managing Partner at Aurelius LLC
Storing relationship data in Cassandra entails data denormalization or pointer chasing inside the application which reduces developer productivity, is error prone, and slow due to lack of optimization. Titan:db exposes a property graph data model directly atop Cassandra which makes storing and querying relationship data fast, easy, and scalable to huge graphs. This talk demonstrates how Titan's features enable complex, multi-relational databases in Cassandra and discusses customer use cases for recommendation and personalization engines.
Titan is a scalable graph database that can distribute and query graph data across multiple machines. This presentation provides a general introduction to graph computing and Titan in particular. It also focuses on some recent development for Titan 0.9 and TinkerPop 3.
A Graph Service for Global Web Entities Traversal and Reputation Evaluation B...HBaseCon
Speakers: Chris Huang and Scott Miao (Trend Micro)
Trend Micro collects lots of threat knowledge data for clients containing many different threat (web) entities. Most threat entities will be observed along with relations, such as malicious behaviors or interaction chains among them. So, we built a graph model on HBase to store all the known threat entities and their relationships, allowing clients to query threat relationships via any given threat entity. This presentation covers what problems we try to solve, what and how the design decisions we made, how we design such a graph model, and the graph computation tasks involved.
C* Summit 2013: Time for a New Relationship - Intuit's Journey from RDBMS to ...DataStax Academy
This session talks about Intuit’s journey of our Consumer Financial Platform that is built to scale to petabytes of data. The original system used a major RDBMS and from there, we redesigned to use the distributed nature of Cassandra. This talk will go through our transition including the data model used for the final product. As with any large system transition, many hard lessons are learned and we will discuss those and share our experiences.
NYC* 2013 — "Using Cassandra for DVR Scheduling at Comcast"DataStax Academy
Comcast is developing a highly scalable cloud DVR scheduling system on top of Cassandra. The system is responsible for managing all DVR data and scheduling logic for devices on the X1 platform. This talk will cover the overall architecture of the scheduling system, data model, message queue and notification software that have been developed as part of this ambitious project. We'll take a deep dive into the details of our data model and review the implementation of Comcast's open-source, Cassandra-based clones of Amazon SQS and SNS.
Cassandra & puppet, scaling data at $15 per monthdaveconnors
Constant Contact shares lessons learned from DevOps approach to implementing Cassandra to manage social media data for over 400k small business customers. Puppet is the critical in our tool chain. Single most important factor was the willingness of Development and Operations to stretch beyond traditional roles and responsibilities.
Titan is an open source distributed graph database build on top of Cassandra that can power real-time applications with thousands of concurrent users over graphs with billions of edges. Graphs are a versatile data model for capturing and analyzing rich relational structures. Graphs are an increasingly popular way to represent data in a wide range of domains such as social networking, recommendation engines, advertisement optimization, knowledge representation, health care, education, and security.
This presentation discusses Titan's data model, query language, and novel techniques in edge compression, data layout, and vertex-centric indices which facilitate the representation and processing of Big Graph Data across a Cassandra cluster. We demonstrate Titan's performance on a large scale benchmark evaluation using Twitter data.
Presented at the Cassandra 2012 Summit.
Big Data for the Rest of Us - OpenWest 2014 - Matt AsayMatt Asay
Everyone wants to launch a Big Data project, but there's still lots of confusion as to how. The key, as this presentation shows, is to minimize the cost of failure and increase iteration, using a strategy based on using well-known open-source tools.
DataStax: Steps to successfully implementing NoSQL in the enterpriseDataStax Academy
NoSQL is the right technology for web, mobile, and IoT applications, but how can you make sure that it's successfully rolled out and implemented in your organization? What are the steps needed for NoSQL to hit the mark and make a difference and what criteria can you use to make the right choice between RDBMS's, NoSQL, and Hadoop?
This sessions covers diagnosing and solving common problems encountered in production, using performance profiling tools. We’ll also give a crash course to basic JVM garbage collection tuning. Attendees will leave with a better understanding of what they should look for when they encounter problems with their in-production Cassandra cluster. This talk is intended for people with a general understanding of Cassandra, but it not required to have experience running it in production.
Cassandra Summit 2014: TitanDB - Scaling Relationship Data and Analysis with ...DataStax Academy
Presenter: Matthias Broecheler, Managing Partner at Aurelius LLC
Storing relationship data in Cassandra entails data denormalization or pointer chasing inside the application which reduces developer productivity, is error prone, and slow due to lack of optimization. Titan:db exposes a property graph data model directly atop Cassandra which makes storing and querying relationship data fast, easy, and scalable to huge graphs. This talk demonstrates how Titan's features enable complex, multi-relational databases in Cassandra and discusses customer use cases for recommendation and personalization engines.
Titan is a scalable graph database that can distribute and query graph data across multiple machines. This presentation provides a general introduction to graph computing and Titan in particular. It also focuses on some recent development for Titan 0.9 and TinkerPop 3.
A Graph Service for Global Web Entities Traversal and Reputation Evaluation B...HBaseCon
Speakers: Chris Huang and Scott Miao (Trend Micro)
Trend Micro collects lots of threat knowledge data for clients containing many different threat (web) entities. Most threat entities will be observed along with relations, such as malicious behaviors or interaction chains among them. So, we built a graph model on HBase to store all the known threat entities and their relationships, allowing clients to query threat relationships via any given threat entity. This presentation covers what problems we try to solve, what and how the design decisions we made, how we design such a graph model, and the graph computation tasks involved.
C* Summit 2013: Time for a New Relationship - Intuit's Journey from RDBMS to ...DataStax Academy
This session talks about Intuit’s journey of our Consumer Financial Platform that is built to scale to petabytes of data. The original system used a major RDBMS and from there, we redesigned to use the distributed nature of Cassandra. This talk will go through our transition including the data model used for the final product. As with any large system transition, many hard lessons are learned and we will discuss those and share our experiences.
NYC* 2013 — "Using Cassandra for DVR Scheduling at Comcast"DataStax Academy
Comcast is developing a highly scalable cloud DVR scheduling system on top of Cassandra. The system is responsible for managing all DVR data and scheduling logic for devices on the X1 platform. This talk will cover the overall architecture of the scheduling system, data model, message queue and notification software that have been developed as part of this ambitious project. We'll take a deep dive into the details of our data model and review the implementation of Comcast's open-source, Cassandra-based clones of Amazon SQS and SNS.
Cassandra & puppet, scaling data at $15 per monthdaveconnors
Constant Contact shares lessons learned from DevOps approach to implementing Cassandra to manage social media data for over 400k small business customers. Puppet is the critical in our tool chain. Single most important factor was the willingness of Development and Operations to stretch beyond traditional roles and responsibilities.
Titan is an open source distributed graph database build on top of Cassandra that can power real-time applications with thousands of concurrent users over graphs with billions of edges. Graphs are a versatile data model for capturing and analyzing rich relational structures. Graphs are an increasingly popular way to represent data in a wide range of domains such as social networking, recommendation engines, advertisement optimization, knowledge representation, health care, education, and security.
This presentation discusses Titan's data model, query language, and novel techniques in edge compression, data layout, and vertex-centric indices which facilitate the representation and processing of Big Graph Data across a Cassandra cluster. We demonstrate Titan's performance on a large scale benchmark evaluation using Twitter data.
Presented at the Cassandra 2012 Summit.
A graph is a data structure composed of vertices/dots and edges/lines. A graph database is a software system used to persist and process graphs. The common conception in today's database community is that there is a tradeoff between the scale of data and the complexity/interlinking of data. To challenge this understanding, Aurelius has developed Titan under the liberal Apache 2 license. Titan supports both the size of modern data and the modeling power of graphs to usher in the era of Big Graph Data. Novel techniques in edge compression, data layout, and vertex-centric indices that exploit significant orders are used to facilitate the representation and processing of a single atomic graph structure across a multi-machine cluster. To ensure ease of adoption by the graph community, Titan natively implements the TinkerPop 2 Blueprints API. This presentation will review the graph landscape, Titan's techniques for scale by distribution, and a collection of satellite graph technologies to be released by Aurelius in the coming summer months of 2012.