Introduction to Cassandra 2, CQL 3, and the Datastax Java Driver Training
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                	 We offer private customized training for groups of 3 or more attendees.
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| Course Description | ||
| The Cassandra (C*) NoSQL database is one of the most powerful and widely
used non-relational databases available today. It is a fault tolerant,
highly scalable database with tunable consistency that meets the
demanding requirements of the "can't fail, must scale" systems
driving growth for many of the most successful enterprises of today.
However, along with that capability comes a new data and programming
model that many organizations lack the expertise to use in an optimal
fashion.  This course provides a technical introduction to all the
conceptual and practical areas needed to use Cassandra successfully. It
is written expressly for the new capabilities in the C* 2.0, including
CQL3.1 and the new DataStax Java driver V2. The course provides a solid
foundation in the architecture and data model of C* and how to work with
it. It covers CQL3 in detail, as well as important data modeling
techniques to optimize your usage of the database. It includes in-depth
coverage of the new Java driver for C*, as well as a full-scale
application based on a stock-trading system (StockWatcher) that uses the
driver.  After taking this course, you will be ready to work with
Cassandra in an informed and productive manner, including using CQL3 and
the new Java driver. You will be aware of some common pitfalls as well
as best practices for creating your data model and applications. You
will gain a clear understanding of how C* works, and be fully prepared
to use it in production systems. 
                        Course Length: 3 Days Course Tuition: $2250 (US) | ||
| Prerequisites | |
| Reasonable Java experience for the Java driver labs, some knowledge of databases | |
| Course Outline | 
| 
 
	Session 1: Introduction to Cassandra 
	Overview 
	The motivation for non-relational data stores 
	Why relational databases don't support modern applications well 
	Cassandra at a high-level 
	Use cases 
	Features Strengths (Scalability, robustness, linear performance with scale-out), etc. 
	High Level Structure 
	Acquiring and Installing Cassandra 
	Configuring and Installation Structure 
	LABS:  
	Configure, Start/Stop Cassandra 
	StockWatcher Demo 
	Session 2: Overview of Architecture and Data Model 
	Basic Cassandra Architecture 
	Cluster Structure - Nodes, Virtual Nodes, Ring Topology 
	Consistent Hashing, Tokens, Partitioners, and Data Distribution 
	Data Replication, the Replication Factor, Keyspaces 
	Consistency, the CAP theorem, Eventual Consistency 
	The C* Data Model 
	Data Model and CQL 3 Introduction 
	Using CQL and cqlsh 
	Single primary key tables and how to define them using CQL 
	Inserting Data (INSERT), Data Distribution in the Ring, Upsert 
	Querying for Data (SELECT) 
	CQL Data Types 
	Working with Primary Keys 
	LABS: 
	Spin up the Lab Cluster 
	Create Simple Tables 
	Insert/Query Tables 
	Use copy to Populate a Table 
	Session 3: The Cassandra Data Model 
	Compound Primary Keys 
	CQL table definition 
	The partition key and clustering columns 
	CQL Mapping vs. Internal Storage View 
	Other Capabilities 
	Expiring Columns / Time To Live (TTL) 
	Batches 
	Clustering order, ORDER BY, and CLUSTERING ORDER BY 
	Filtering results and ALLOW FILTERING 
	Composite Partition Keys 
	Motivation and uses 
	CQL Definition 
	Effect on Partitioning and Internal Storage View 
	Indexes and Secondary Indexes 
	Partition Key Indexes, token() 
	Non-primary Key (Secondary) Indexes 
	Guidelines and Querying 
	Understand and Use Counters 
	Motivation and Uses 
	Structure, Characteristics, CQL, Usage 
	Limitations 
	Understand and use collections 
	Motivation and uses 
	CQL definition (set, list, and map) 
	Inserting, Updating, Deleting with a Collection 
	Limitations and Internal Storage View 
	LABS: 
	Introduce Compound Primary Keys 
	Refine Compound Primary Key 
	Work with Composite Partition Keys 
	Secondary Indexes 
	Counters 
	Using Collections 
	Session 4: Data Consistency 
	Data Consistency in Cassandra 
	Tunable Consistency 
	CAP Theorem 
	Coordinators and Client Requests 
	Consistency Levels in C* - ONE, QUORUM, ALL 
	Configuring Immediate Consistency 
	CL ONE is Your Friend 
	Other CL Levels 
	Compare and Set (CAS) / Lightweight Transactions 
	Motivation and Need 
	Overview of CAS 
	Using CAS - IF NOT EXISTS, IF condition 
	Paxos - How CAS works 
	Overhead and caveats 
	Static Columns 
	Overview 
	Declaring Tables and Using Static Columns 
	Guidelines and Uses 
	Repair Mechanisms 
	Read Repair 
	Hinted Handoff 
	LABS: 
	Data Consistency 
	CAS 
	Session 5: How Things Work 
	Write Failures 
	Unavailability, Node Failure 
	Requirements for Writing 
	Key and Row Caches 
	Cache Overview 
	Guidelines 
	Multi-Data Center Support 
	Overview 
	Replication Factor Configuration 
	Consistency Levels - LOCAL/EACH QUORUM 
	Deletes 
	CQL 
	Tombstones 
	Issues and Guidelines 
	LABS: 
	Deletes 
	Session 6: The Java Driver 
	Introduction 
	Overview and Architecture 
	Features 
	API Introduction 
	Cluster and Cluster.Builder 
	Creating the Cluster 
	Contact Points 
	Getting a Session 
	Working with Sessions 
	Querying 
	PreparedStatement, Statement, BoundStatement 
	Using PreparedStatements, Binding Values 
	Executing the Query 
	Processing Query Results 
	CQL to Java Type Mapping 
	Working with UUIDs 
	Setting Consistency Level 
	QueryBuilder and Dynamic Queries 
	Dynamic Queries 
	Bind Variables and SimpleStatement 
	QueryBuilder - Fluent API for Queries 
	Building SELECT, Select Type, Select.where(), Chaining WHERE Clauses 
	Building DELETE, Delete Type, Delete.where() 
	Building INSERT, Insert Type, Insert.insertInto(), Insert.value() 
	Building Update, Update Type, Insert.with(), Insert.value() 
	Building Regular Batches and Prepared Statement Batches (BatchStatemnt) 
	Other Queries 
	Asynchronous Querying 
	Normal vs Asynchronous Querying 
	Interface java.util.concurrent.Future 
	ResultSetFuture 
	Querying Asynchronously and Processing Future Results 
	Listeners for Processing 
	Driver Policies 
	Overview 
	Load Balancing Policies - RoundRobinPolicy, DCAwareRoundRobinPolicy 
	Retry Policies - DefaultRetryPolicy, DowngradingConsistencyRetryPolicy, LatencyAwarePolicy 
	The Policies Class 
	LABS: 
	Introducing StockWatcher (the Lab Domain) 
	Connect to a Cluster 
	Execute Queries 
	Use QueryBuilder for Select 
	Use QueryBuilder More Extensively 
	Use executeAsync() and ResultSetFuture 
	Use Driver Policies 
	StockWatcher Deep Dive - Examining a Full-fledged Application | 
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