Download E-books Learning Apache Cassandra - Manage Fault Tolerant and Scalable Real-Time Data PDF

Key Features

  • Learn how you can set up and use Cassandra from the floor up
  • Design wealthy schemas that trap the relationships among varied information forms utilizing compound fundamental keys
  • Master the complex positive aspects on hand in Cassandra 2.0 via a step by step instructional that builds a real-world application's database layer.

Book Description

Cassandra is a dispensed database that sticks out for its strong characteristic set and intuitive interface, whereas nonetheless delivering the excessive availability and scalability of a disbursed store.

Starting from fitting Cassandra and growing your first keyspace, to gaining knowledge of the several desk constructions Cassandra bargains and exploring the newest and strongest gains of the Cassandra question Language, CQL3, this publication explores each one subject in the course of the lens of a real-world instance software. With lots of examples, information, and transparent motives, you are going to grasp compound fundamental keys, assortment columns, light-weight transactions, and plenty of different complex elements of Cassandra.

By the top of the publication, you will be totally outfitted to construct robust, scalable Cassandra database layers to your applications.

What you are going to learn

  • Install Cassandra and create your first keyspace
  • Choose the appropriate desk constitution for the duty to hand in numerous scenarios
  • Use diversity slice queries for effective info access
  • Effortlessly deal with concurrent updates with assortment columns
  • Ensure info integrity with light-weight transactions and logged batches
  • Understand eventual consistency and use the ideal consistency point to your situation
  • Implement top practices for info modeling and access

About the Author

Mat Brown is a qualified software program engineer in Brooklyn, manhattan. In his occupation, he has concerned about construction consumer-facing net and cellular functions for a number of businesses; he at present works at Genius.

Table of Contents

  1. Getting up and working with Cassandra
  2. The First Table
  3. Organizing similar Data
  4. Beyond Key-value Lookup
  5. Establishing Relationships
  6. Denormalizing info for max Performance
  7. Expanding Your info Model
  8. Collections, Tuples, and User-defined Types
  9. Aggregating Time-series Data
  10. How Cassandra Distributes Data

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Updates can create new rows The INSERT statements will not be the single write operations in CQL which can have unforeseen results. to work out how replace can take us all of sudden, let's replace gina's row so as to add a position: replace "users" SET "location" = 'Houston, TX' the place "username" = 'gina'; Wait a second—who's gina? up to now, we have not had a person with the username gina in our desk. we would count on the previous replace assertion to don't have any impact: in the end, our the place assertion specifies a row that doesn't exist. The contents of the clients desk, notwithstanding, inform a special tale: there's now a row with the first key gina. It seems that an replace assertion, similar to an INSERT assertion, is in reality an upsert operation: if the desired row exists, it's going to replace values within the row, but when it does not, a brand new row could be created. because it seems, of their simple varieties, the INSERT and replace queries are syntactic editions of the very same underlying operation. for example, the next queries are functionally just like each other: INSERT INTO "users" ("username", "email", "encrypted_password") VALUES ('alice', 'alice@gmail. com', 0x8914977ed729792e403da53024c6069a9158b8c4); replace "users" SET "email" = 'alice@gmail. com', "encrypted_password" = 0x8914977ed729792e403da53024c6069a9158b8c4 the place "username" = 'alice'; In either situations, the question easily instructs Cassandra to set the e-mail and encrypted_password columns to the given values within the row whose fundamental key's alice. INSERT and replace aren't completely redundant; in spite of the fact that, each one offers sure functions that the opposite doesn't. for example, purely INSERT helps the IF no longer EXISTS clause that we explored prior. replace queries even have distinct performance, now not the least of that's conditional updates. confident locking with conditional updates because the MyStatus provider turns into extra well known, we are prone to see organisations starting to create debts which are controlled via a number of humans. when we have a number of humans getting access to an identical source even as, we have to take into consideration what may get it wrong whilst assorted humans try and make conflicting alterations to a similar piece of information. Let's create a brand new account on behalf of a firm referred to as HappyCorp. we will simply commence with a few simple details: INSERT INTO "users" ("username", "email", "encrypted_password") VALUES ('happycorp', 'media@happycorp. com', 0x368200fa910c16cc644f3512e63b541c85fa2a3c) IF now not EXISTS; We use a conditional replace, after all, to make sure that we aren't overwriting one other row with an analogous basic key. Now, lets say that contributors of the HappyCorp social media crew choose to replace the site indexed within the company's profile on MyStatus while. considered one of them elects to go into manhattan, the positioning of HappyCorp's company workplaces, and the opposite thinks it will make extra feel to record Palto Alto, the place the company's major R&D campus is found. regrettably, the 2 staff choose to make this replace on the very same time; so each sees a clean situation box, forms a cost in, and attempts to reserve it with out understanding that they're stomping on every one other's paintings.

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