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Learning Cypher
Learning Cypher

Learning Cypher: Write powerful and efficient queries for Neo4j with Cypher, its official query language

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Profile Icon Onofrio Panzarino
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Full star icon Full star icon Full star icon Half star icon Empty star icon 3.7 (12 Ratings)
Paperback May 2014 162 pages Edition
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NZ$24.99 NZ$35.99
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Arrow left icon
Profile Icon Onofrio Panzarino
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Free Trial
Full star icon Full star icon Full star icon Half star icon Empty star icon 3.7 (12 Ratings)
Paperback May 2014 162 pages Edition
eBook
NZ$24.99 NZ$35.99
Paperback
NZ$43.99
Subscription
Free Trial
eBook
NZ$24.99 NZ$35.99
Paperback
NZ$43.99
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Learning Cypher

Chapter 2. Filter, Aggregate, and Combine Results

In the previous chapter, we learned the basics of Cypher querying, including pattern matching. To use Cypher in real-world applications, you'll need a set of features, which we are going to cover in this chapter. These features include searching by text in the database, data aggregation for statistical analysis, pagination for performance improvements, or even simple filtering on an array of properties.

Filtering


Pattern matching is useful to describe the data we are looking for and how nodes and relations are organized in the graph database. However, we often need to filter data in more detail.

The book store – an example

In this chapter, we'll learn how to filter results using a real-world example: the book store. Just as we saw in the previous chapter, we have to define labels and relationships. A minimal set of labels are as follows:

  • Book: This label includes all the books

  • Person: This label includes authors, translators, reviewers, and so on

  • Publisher: This label includes the publishers of books in the database

  • User: This label includes the users of the website

A set of basic relationships are as follows:

  • PublishedBy: This relationship is used to specify that a book was published by a publisher

  • Votes: This relationship describes the relation between a user and a book, for example, how a book was rated by a user

Every book has the following properties:

  • Title: This is the title of the book...

Sorting


If you have experience with SQL, then sorting with Cypher is exactly the same as sorting with SQL. We can use the ORDER BY clause to specify the columns to be used for sorting, as shown in the following query:

MATCH (b:Book)
WHERE ANY ( tag IN b.tags WHERE tag IN ['drama'] )
RETURN b.title
ORDER BY b.title
LIMIT 5

The preceding query looks for books tagged drama in the database, then sorts them by title, and returns the first five book entries found. We can note the following:

  • The ORDER BY clause follows the RETURN clause

  • This clause is above the LIMIT or SKIP clause so that we can sort the data before limiting our page

The result set is as follows:

+-----------------------------+
| b.title                     |
+-----------------------------+
| "A Lover's Complaint"       |
| "A Midsummer Night's Dream" |
| "All's Well That Ends Well" |
| "Anthony and Cleopatra"     |
| "As You Like It"            |
+-----------------------------+

A descending sort

To sort inversely, just postpone the DESC...

Aggregating results


In our application, we have users who rate books with a score from one to five. Now, we are going to query the database to get some aggregated information about book scores.

Counting matching rows or non-null values

Suppose that we want to know the number of users who have voted for a book. For this, we need to count the number of the vote relations between the users and that book, as shown in the following code snippet:

START b=node({id})
MATCH (b) <-[r:Vote]- (u:User)
RETURN COUNT(*) as votes

The only difference with the query patterns we already know is that here, we have used the COUNT function in the RETURN clause. With Cypher, the RETURN clause drives the aggregation of entities. In this case, as we have nothing else in the RETURN clause but the COUNT function, all the matching results are counted and the result is a single value. The result is as shown in the following output code:

+-------+
| votes |
+-------+
| 7     |
+-------+
1 row

The arguments inside the COUNT...

The UNION statement


Suppose we want to know how many books and how many authors are stored in our database. We can perform two queries to get these values, but with the UNION statement, we can merge these data together. Just put the UNION keyword between two or more queries, as shown in the following query:

MATCH (b:Book)
RETURN 'Books' as type, COUNT(b) as cnt
UNION ALL
MATCH (a:Person)
RETURN 'Authors' as type, COUNT(a) as cnt

The result is as follows:

+-----------------+
| type      | cnt |
+-----------------+
| "Books"   | 150 |
| "Authors" | 142 |
+-----------------+

The only condition we must be careful of with the UNION statement is that the result set must have the same number of columns and the columns must have the same names.

You're perhaps wondering why we used the UNION ALL statement and not the UNION statement in the previous example. There is a subtle difference between them—the UNION statement removes duplicated rows after merging results, so it is slower.

Tip

If you don't care...

Summary


In this chapter, you learned some advanced techniques to query a Neo4j database. First of all, we used the WHERE statement to filter data. Text values can be filtered using regular expressions, which are very flexible and powerful tools to work with strings. Numbers can be filtered using mathematical operators and functions. Logical expressions can be built using Boolean operators (OR, AND, XOR, and NOT). Collections can be filtered using collection predicates.

Paging data is an important feature for a database, especially when it can be very large. You learned how to page data using the LIMIT and SKIP keywords. An important part of this chapter is about aggregating. You learned how to use the RETURN clause to aggregate data with the most common aggregation functions, especially COUNT, SUM, AVG, MAX, and MIN. Finally, we took a look at two useful features of this language: the WITH and UNION keywords. The WITH keyword is used to split queries in order to make them easier to write...

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What you will learn

  • Design and create flexible and fast graph databases using the Cypher declarative syntax
  • Write powerful, readable, and reusable queries with pattern matching and parameters
  • Develop fast applications using best practices to improve the performance of your Cypher queries
  • Transition smoothly from SQL to Neo4j
  • Migrate relational databases to the graph model, getting rid of O/R mismatch
  • Avoid the common mistakes and pitfalls in programming with Neo4j

Product Details

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Publication date, Length, Edition, Language, ISBN-13
Publication date : May 14, 2014
Length: 162 pages
Edition :
Language : English
ISBN-13 : 9781783287758
Category :

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Product Details

Publication date : May 14, 2014
Length: 162 pages
Edition :
Language : English
ISBN-13 : 9781783287758
Category :

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Table of Contents

5 Chapters
Querying Neo4j Effectively with Pattern Matching Chevron down icon Chevron up icon
Filter, Aggregate, and Combine Results Chevron down icon Chevron up icon
Manipulating the Database Chevron down icon Chevron up icon
Improving Performance Chevron down icon Chevron up icon
Migrating from SQL Chevron down icon Chevron up icon

Customer reviews

Top Reviews
Rating distribution
Full star icon Full star icon Full star icon Half star icon Empty star icon 3.7
(12 Ratings)
5 star 33.3%
4 star 16.7%
3 star 33.3%
2 star 16.7%
1 star 0%
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TAL Oct 12, 2017
Full star icon Full star icon Full star icon Full star icon Full star icon 5
Very methodology learning
Amazon Verified review Amazon
Kozhanov Eugeny Aug 31, 2014
Full star icon Full star icon Full star icon Full star icon Full star icon 5
This is great book! It's easy to read and learning Cypher. It's have examples of queries and examples code using Cypher's queries in Java. This book very useful for SQL users, because it's easy to learn if you use SQL in your work. There are examples and comments for each query in this book. I use neo4j and Java, and this book help me make my queries more shorter and useful for other developers in our team.
Amazon Verified review Amazon
Deven Kalra Sep 23, 2014
Full star icon Full star icon Full star icon Full star icon Full star icon 5
Seamlessly upgrade from SQL to Cypher.. Author has in depth knowledge of the subjects and he explains about graph theory also.. So need to purchase additional book for that.. Basically all the code is in java so if you are trying to connect to Graph database like Neo4J you are in luck with this! I know I was. Hitting wall after wall.. till I found this gem. Very cheap and good.
Amazon Verified review Amazon
Daniele Ticchiarelli Jun 25, 2014
Full star icon Full star icon Full star icon Full star icon Full star icon 5
The authors have done an outstanding job of extracting the essence of Cypher and describing a core set of features of the tool features as well as how to take advantage from them.He describes very clearly his capability, constructs and above all how to manage with the relationships among nodes, their creation, modification and deleting.This text has served as a helpful guide among other more recently online docs and tutorials.Yes, I would recommend it.
Amazon Verified review Amazon
online shopper Feb 25, 2015
Full star icon Full star icon Full star icon Full star icon Empty star icon 4
I've been playing with Neo4j off and on for more than a year, and I knew that Cypher was maturing as a query language.I agree with the other reviewer who said there's a bunch of java stuff at the beginning, which may be useful. I don't know because I'm still learning java.But I was surprised to find that since Cypher is so intuitive, that if you just jump into Chapter 1, around page 20, if you're familiar with graphs and databases, it should be pretty obvious what is going on from the syntax alone.Having said that, I found the comparisons with SQL really helpful. I was surprised to note how many of the things in this book were already familiar to me, and how many new features have been added to Cypher.I hope it will continue growing as a language, since there are still a lot of graph applications that require outside wrappers (I use py2neo), and not all of those wrappers are fully developed, yet. So java is the fallback for anything sophisticated you might want to do.This book is really for those who are newer to Neo4j and want to get up and running quickly with a good overview of what it can do out of the box, which is quite a lot.
Amazon Verified review Amazon
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