Learning Cypher

By Onofrio Panzarino

Write robust and effective queries for Neo4j with Cypher, its legitimate question language

About This Book

  • Improve functionality and robustness should you create, question, and hold your graph database
  • Save time via writing robust queries utilizing trend matching
  • Step-by-step directions and useful examples that will help you create a Neo4j graph database utilizing Cypher

Who This ebook Is For

If you must tips on how to create, question, and preserve a graph database, or are looking to migrate to a graph database from SQL, this is often the ebook for you.

What you'll Learn

  • Design and create versatile and speedy graph databases utilizing the Cypher declarative syntax
  • Write strong, readable, and reusable queries with development matching and parameters
  • Develop quick purposes utilizing top practices to enhance the functionality of your Cypher queries
  • Transition easily from SQL to Neo4j
  • Migrate relational databases to the graph version, casting off O/R mismatch
  • Avoid the typical error and pitfalls in programming with Neo4j

In Detail

Neo4j is producing a lot curiosity between NoSQL database clients for its gains, functionality and scalability, and robustness. The software program additionally offers clients with a truly traditional and expressive graph version and ACID transactions with rollbacks. even though, using Neo4j in a real-world undertaking might be tough in comparison to a conventional relational database. Cypher fills this hole with SQL, delivering a declarative syntax and the expressiveness of trend matching. This quite easy yet robust language helps you to specialise in your area rather than getting misplaced in database entry. As you are going to study during this publication, very complex database queries can simply be expressed via Cypher.

This booklet is a pragmatic, hands-on consultant to designing, enforcing, and querying a Neo4j database fast and painlessly. via a few sensible examples, this e-book uncovers the entire behaviors to help you to exploit Neo4j successfully, with advice and tips to assist you alongside the way in which. The publication begins with the elemental clauses and styles to accomplish read-only queries with Cypher. you'll then know about clauses and information that may be used with styles to intricate effects coming from development matching. subsequent, you'll grasp the clauses required to switch a graph. upon getting received those fundamentals correct with assistance from functional examples, you are going to then find out about instruments and practices to enhance the functionality of queries and the way emigrate a database to Neo4j from the floor up. to complete off, the booklet covers Cypher operators and capabilities in detail.

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Occasionally, I used the HR administration device database (from bankruptcy 1, Querying Neo4j successfully with trend Matching) while it'd be extra applicable. to attempt out the code, you could arrange the database with the scripts, you could obtain from the Packt Publishing web site (http://www. packtpub. com/support). Operators The operators are grouped by means of class. such a lot of them go back a null worth if any operand has a null price. besides, there are a few exceptions. So, for every operator, the habit in case of a null price operand is certain. comparability operators comparability operators are binary operators that go back a Boolean or a null price as effects. they're normally utilized in the the place clause (see bankruptcy 2, clear out, mixture, and mix effects, for info) to clear out info in response to a , even if they are often utilized in the go back clause besides. In Cypher, comparability operators may be grouped in periods: ordering operators and equality operators. Operators and services Ordering operators Ordering operators are used to check values (usually estate values or literals). they're as follows: Operator < Description <= under or equivalent to > more than >= more than or equivalent to lower than let's examine an instance utilizing this sort of operators. this question seems for all books released in 2012 or later. If a PublishedBy courting does not have the yr estate set, will probably be discarded. The question is as follows: fit (a:Book)-[r:PublishedBy]-(b:Publisher) the place r. 12 months >= 2012 go back a,r,b be aware the subsequent results: • basically numbers and string values are supported. • evaluating any price to a null price will lead to a null worth. for instance, the entire following expressions will provide a null worth: °° 1 < NULL °° NULL < "String" °° NULL < NULL • evaluating nodes or relationships is an unlawful operation. it is going to lead to a syntax blunders. • evaluating numbers of alternative forms (a double price with an integer worth or an extended worth with an integer worth) is supported; in spite of the fact that, numbers can be switched over earlier than being in comparison. • evaluating arrays isn't really supported. • evaluating numbers to thread values will generate a runtime blunders. in the event you have no idea even if a estate is a host within the dataset and if a string comparability is adequate, you could lodge to the STR functionality (this is roofed later during this appendix). [ 124 ] Appendix Equality operators Equality operators are used to check the equality of 2 values. They go back a Boolean worth or a null price. they're as follows: • = returns real if the 2 values are equivalent • <> returns real if the 2 values are usually not equivalent the subsequent question returns the books that experience the desired identify: fit (a:Book) the place a. name = "Learning Cypher" go back a word the next: • evaluating any worth to a null price will lead to a null price. to check null values, use the NULL equality operators pointed out within the subsequent part. for instance, the entire following expressions will supply a null price because the consequence: °° 230.

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