Mongodb Recipes - by Subhashini Chellappan & Dharanitharan Ganesan (Paperback)
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<p/><br></br><p><b> Book Synopsis </b></p></br></br><p><b>Chapter 1: MongoDB Features and Installation</b></p> <p>Chapter Goal: In this chapter, you will learn NoSQL databases, CAP theorem, MongoDB Features and MongoDB tools. This chapter will also cover installation of MongoDB and its associated tools.</p> <p>Sub Topics: </p> <p>NoSQL Databases and Categories</p> <p>CAP Theorem</p> <p>MongoDB Features</p> <p>MongoDB Tools</p> <p>Describe JSON and BSON</p> <p>Installing MongoDB on Windows, Linux</p> <p>MongoDB Terms</p> <p>MongoDB Data Types</p> <p><b>Chapter 2: CRUD Operations</b></p> <p>Chapter Goal: In this chapter, you will learn how to perform CRUD operations with MongoDB. This chapter also help you to understand how to query embedded documents and arrays.</p> <p>Sub Topics: </p> <p>Basic CRUD operations</p> <p>Query Embedded Documents</p> <p>Query Arrays</p> <p>Bulk Write Operations</p> <p> </p> <p><b>Chapter 3: Data Modelling</b></p> <p>Chapter Goal: In this chapter, you will learn schema design and various data modelling patterns in MongoDB.</p> <p>Sub Topics: </p> <p>Data Modelling Concepts</p> <p>Data Model Patterns</p> <p>Model Relationship between documents</p> <p>Model Tree Structures</p> <p> </p> <b>Chapter 4: Indexing and Aggregation Framework</b><p></p> <p>Chapter Goal: In this chapter, you will learn indexes types and Aggregation Framework in MongoDB.</p> <p>Sub Topics: </p> <p>Introduction to indexes</p> <p>Index Types</p> <p>Creating Indexes</p> <p>Introduction to Aggregation Framework</p> <p>Aggregation Framework Types</p> <p> </p> <p><b>Chapter 5: MongoDB Replication and Sharding</b></p> <p>Chapter Goal: In this chapter, you will learn the replication set up and sharding set up.</p> <p>Sub Topics: </p> <p>Replication Concepts</p> <p>Master Slave Replication</p> <p>Replication Setup</p> <p>Introduction to Sharding and concepts</p> <p>Shard Setup</p> <p>Types of Sharding</p> <p> </p> <p><b>Chapter 6: MongoDB Transaction</b></p> <p>Chapter Goal: In this chapter, you will learn transactions in MongoDB.</p> <p>Sub Topics: </p> <p>Atomicity</p> <p>Multi-Document Transaction</p> <p>Concurrency Control</p> <p> </p> <p><b>Chapter 7: MongoDB Administration</b></p> <p>Chapter Goal: In this chapter, you will learn Database Profiler, MongoDB Backup Methods and Monitoring MongoDB.</p> <p>Sub Topics: </p> <p>Database Profiler</p> <p>MongoDB Backup Methods</p> <p>Monitoring MongoDB</p> <p> </p> <p><b>Chapter 8: MongoDB Security</b></p> <p>Chapter Goal: In this chapter, you will learn security aspects of MongoDB.</p> <p>Sub Topics: </p> <p>Creating Users</p> <p>Creating and Assigning custom roles</p> Authenticating Server<p></p><br><p/><br></br><p><b> From the Back Cover </b></p></br></br>Get the most out of MongoDB using a problem-solution approach. This book starts with recipes on the MongoDB query language, including how to query various data structures stored within documents. These self-contained code examples allow you to solve your MongoDB problems without fuss.<br><i>MongoDB Recipes</i> describes how to use advanced querying in MongoDB, such as indexing and the aggregation framework. It demonstrates how to use the Compass function, a GUI client interacting with MongoDB, and how to apply data modeling to your MongoDB application. You'll see recipes on the latest features of MongoDB 4 allowing you to manage data in an efficient manner using MongoDB.<br>You will: <ul><li>Work with the MongoDB document model <br></li><li>Design MongoDB schemas <br></li><li>Use the MongoDB query language<br></li><li>Harness the aggregation framework<br></li><li>Create replica sets and sharding in MongoDB</li></ul><p/><br></br><p><b> About the Author </b></p></br></br><b>Subhashini Chellappan</b> is a technology enthusiast with expertise in the big data and cloud space. She has rich experience in both academia and the software industry. Her areas of interest and expertise are centered on business intelligence, big data analytics and cloud computing.<br><b>Dharanitharan Ganesan</b> is an MBA in Technology management with high level of exposure and experience in big data - Apache Hadoop, Apache Spark and various Hadoop ecosystem components. He has a proven track record of improving efficiency and productivity through the automation of various routine and administrative functions in business intelligence and big data technologies. His areas of interest and expertise are centered on machine learning algorithms, Blockchain in Bigdata, statistical modelling and predictive analytics. <p/><br>
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