Neo4j Cypher: Getting started! | Neo4j Tutorial
Summary
TLDRこのビデオスクリプトでは、Neo4jデータベースからデータを取得するためのCypherクエリ言語の基本について解説しています。プロパティグラフモデルの要素であるノードとリレーションシップ、そしてそれらに関連するプロパティについて理解を深めながら、Cypherの人間らしい可読性の高い構文を紹介しています。簡単なグラフの例を通じて、Cypherでグラフを表現し、ノードとリレーションシップをクエリで参照する方法を学びます。次に、Cypherのキーワードや高度なクエリの書き方、ループやサブクエリなどの複雑な概念に触れる次のレクチャーに期待しましょう。
Takeaways
- 🌐 CypherはNeo4jデータベースでデータを取得するためのクエリ言語であり、グラフデータモデルを効果的に操作するために使用されます。
- 🔍 Cypherは人間が理解しやすいようにデザインされており、英語の文法や記号学に基づいています。
- 📚 ノードとリレーションシップはプロパティグラフモデルの基本であり、Cypherクエリ言語で簡単に表現できます。
- 🎯 Cypherはパターン認識に基づいていて、データ内の単純または複雑なパターンを見つけることができます。
- 📝 Cypherのシンタックスは非常に視覚的に理解しやすく、実際のグラフの見た目と同様の構造を持っています。
- 👤 ノードはデータエンティティを表し、Cypherクエリ言語で括弧()で表現します。
- 🔗 リレーションシップはノード間の接続を表し、Cypherでは矢印や四角形のブラケット[]で表現されます。
- 🏷️ ノードやリレーションシップには変数を割り当てて、後のステップで参照できます。
- 📑 ノードとリレーションシップのプロパティは中括弧{}を使ってCypherクエリ言語で表現され、詳細情報を提供します。
- 🔑 Cypherのキーワードはデータの取得に不可欠で、次回の講座ではそれらについて学ぶ予定です。
- 📚 初心者から上級者まで、Cypherクエリの書き方や複雑な構文、ループ、サブクエリなどについて学ぶことができます。
Q & A
Cypherとはどのようなデータベースクエリ言語ですか?
-CypherはNeo4jデータベースによって使用されるグラフデータベースクエリ言語で、ノードとリレーションシップを用いてデータを問い合わせます。人間が理解しやすいようにデザインされており、英語の文法に基づいています。
なぜCypherは他のプログラミング言語ではなく、データベースクエリに使用されるのですか?
-Cypherはグラフデータベースの性質に適しており、ノードとリレーションシップの組み合わせを簡単に表現できるためです。また、視覚的なデータに対する人間の脳の特性を利用しており、パターン認識が基本となっています。
プロパティグラフモデルとは何ですか?
-プロパティグラフモデルはノードとリレーションシップから成り立ち、それぞれのノードやリレーションシップにプロパティ(キーバリューペア)を持ち、複雑なデータ構造を表すことができます。
Cypherにおけるノードとリレーションシップはどのように表現されますか?
-ノードは丸括弧で、リレーションシップは角括弧で表現されます。ノードにはデータエンティティを、リレーションシップにはノード間の接続を表すことができます。
Cypherクエリでノードに変数を割り当てる方法はどのようなものですか?
-ノードに変数を割り当てるには、ノードの丸括弧内で変数名を指定します。例えば、`(person:Person {name: 'Jennifer'})` のように変数名を指定することで、後で参照ができます。
Cypherクエリでリレーションシップに変数を割り当てることはできますか?
-はい、リレーションシップにも変数を割り当てることができます。これはリレーションシップの角括弧内で変数名を指定することで行われます。
Cypherクエリでノードのラベルはどのように機能しますか?
-ノードのラベルは、グラフ内のノードを分類するために使用され、特定のタイプのノードをグループ化するのに役立ちます。例えば、映画データセットでは、映画、俳優、監督などの異なる種類のノードにラベルを付けることができます。
Cypherクエリでリレーションシップのプロパティをどのように表現しますか?
-リレーションシップのプロパティは、リレーションシップの角括弧内の波括弧で表現されます。例えば、`-[:FRIENDS {since: 2018}]-` のように、`FRIENDS` リレーションシップに `since` というプロパティを追加することができます。
Cypherクエリの基本的なキーワードには何がありますか?
-Cypherクエリの基本的なキーワードには `MATCH`, `RETURN`, `WHERE`, `CREATE` などがあります。これらを使ってグラフ内のデータの検索、フィルタリング、作成を行うことができます。
Cypherクエリ言語を学ぶ際に理解すべき基本的なコンセプトは何ですか?
-Cypherクエリ言語を学ぶ際には、ノード、リレーションシップ、変数、ラベル、プロパティ、そしてパターン認識などの基本的なコンセプトを理解することが重要です。これにより、効果的にデータベースを操作し、複雑なクエリを作成することができます。
Cypherクエリで複雑なパターンを検索する方法はありますか?
-はい、Cypherクエリ言語は複雑なパターン検索に対応しており、グラフ内のデータ構造を効果的にトラバースすることができます。ループやサブクエリのような高度な機能も利用可能です。
Outlines
😀 Cypher言語の基本とデータ取得方法
この段落では、Neo4jデータベースからデータを取得するためのCypher言語の基本について説明しています。Cypherはプロパティグラフモデルを利用し、ノードとリレーションシップを組み合わせることで強力なグラフを作成します。Cypherの構文は人間が読みやすいように設計されており、英語の文法や記号を使っています。例えば、Jenniferという人物がグラフ技術を好むという関係をCypherクエリに変換することができます。この段落では、ノードとリレーションシップをCypherクエリにどのように表現するかについて学びます。
📚 Cypherクエリのノードとラベルの使い方
この段落では、Cypherクエリでノードを表現する方法と、ノードラベルの重要性について説明しています。ノードはデータエンティティを表し、例えば人物や企業などの名詞やオブジェクトで識別できます。ノードラベルは、プロパティグラフモデル内のノードをグループ化するのに役立ちます。例えば、映画データセットでは映画、俳優、監督などの異なる種類のノードをラベルでグループ化することができます。ノードラベルはリレーショナルデータベースのテーブル名に似ており、関連するデータを整理するのに役立ちます。
🔗 Cypherクエリにおけるリレーションシップとプロパティ
この段落では、Cypherクエリでリレーションシップとノードのプロパティをどのように表現するかについて学びます。リレーションシップはグラフ内のノードを接続し、特定の方向性を持つことができます。例えば、「likes」や「friends with」、「works for」などのリレーションシップタイプがあります。リレーションシップのプロパティは、リレーションシップに追加のデータや詳細を提供します。Cypherクエリでは、ノードのプロパティを丸括弧で、リレーションシップのプロパティを波括弧で表現します。このセクションでは、これらの概念を理解し、Cypherクエリでそれらをどのように使用するかについて説明しています。
Mindmap
Keywords
💡Cipher
💡ノード (Node)
💡リレーションシップ (Relationship)
💡プロパティ (Property)
💡パターン (Pattern)
💡可読性 (Readability)
💡変数 (Variable)
💡ノードラベル (Node Label)
💡アイコノグラフィ (Iconography)
💡クエリ (Query)
Highlights
讲座介绍了如何在Windows PC上设置4G,并讨论了Cypher查询语言的基础知识。
Cypher是Neo4j数据库使用的查询语言,它与SQL等其他编程语言不同。
属性图模型由节点和关系组成,可以通过属性来增加上下文。
模式识别是大脑工作的基础,Cypher基于模式寻找数据中的简单或复杂模式。
Cypher的语法设计易于人类阅读,基于英语语法和图标学。
通过简单示例展示了如何将图转换为可读的英文短语。
介绍了如何在Cypher中表示节点,使用圆括号和变量。
讨论了节点标签的概念,类似于关系数据库中的表名。
解释了如何在Cypher中表示关系,包括关系类型和方向。
展示了如何在Cypher查询中使用关系变量来引用后续步骤。
讨论了节点和关系的属性,以及如何在Cypher中使用花括号表示它们。
强调了为节点和关系分配变量的重要性,以便在查询中进一步使用。
预告了下一讲将介绍Cypher的关键词和基础语法。
提到了将从基础到高级逐步讲解Cypher查询的编写。
预告了将涵盖循环、子查询等复杂主题的高级Cypher查询。
鼓励观众订阅频道并在评论区提出困难以便进一步讨论。
Transcripts
hello and welcome back to the channel I
hope you have set up your new 4G on your
Windows PC so that we have seen in the
previous lecture so this lecture is all
about Cipher fundamental and how we can
write a query to fetch the data from the
neo4j database so without further Ado
let's get into it okay so before jumping
on to writing queries we need to First
understand what exactly is Cypher and
why we are using Cipher query language
instead of any other programming
language like SQL so let's discuss that
now we already know that a property
graph model which is leveraged by neo4j
database is comprised of different kinds
of nodes and relationship and we will be
also having some properties so we can
relate it to as a key value pairs of
data in our nodes or it can also be
present in the relationship to add more
context into your graph so this may
sound simple so the simple combination
of nodes and relationship really makes
the powerful property graph model and if
you talk about the patterns patterns are
nothing but the combination of these
nodes and relationship which can
represent simple as well as the complex
graph traversals or the parts that we
are going to see in the next lecture so
pattern recognition is like the
fundamental of how our brain works our
brain likes the visual data it's like
for example visual diagrams or any
memory matching game so Cipher is also
based on these patterns and finding the
simple or complex patterns inside your
data so this will make Cipher a very
simple and logical language to learn for
every developer so if we talk about the
cipher syntax as you can see here Cipher
is like designed to be very human
readable so its construct is like based
on English Pros as well as the
iconography so we can easily convert any
data any nodes and relationships into
the cipher query because its syntax will
be similar to how we see that in our
actual graph and it makes the syntax
vary visually and easily understandable
so let's talk about it with some simple
example
so as you can see here we got a very
simple graph in which we have the person
node company and the technology node and
we also have different properties which
is name in the person node as well as in
company as well as in the technology we
have the property as a type and we have
the relationships between all these
nodes
so as you can see we can easily convert
this graph into like a readable English
phrases so as you can see we can say it
as these Jennifer person likes graph so
graph is nothing but a technology and we
have the likes relationship between
these two nodes as well as we can say it
as Jennifer is friends with this person
which is another person which is Michael
and also Jennifer works for neo4j so we
have converted this graph into the
English phrases so the next step would
be we want to convert it into the cipher
and we are going to see it in the
further lectures where we will see what
is like a cipher keywords and how we can
convert this graph into a cipher query
language to fetch different patterns
using your data so as we already know
that the nodes and relationships are the
fundamental components of every property
graph model so as you can see here how
we can represent nodes in the cipher so
it is very simple if we talk about the
previous examples only we had like the
four nodes as well as relationships
present so as you can see we got the
four nodes here so nodes are nothing but
which represents the data entity in your
graph and you can identify the nodes in
your graph using the nouns or objects so
as you can see we got the two person
which are named Michael as well as
Jennifer respectively and we also have
like the company and Technology entities
which represents the neo4j node as well
as the graph node which is the type of
technology so this is how you can
represent nodes using the cipher query
language so to sum it up in our graph
Michael neo4j Jennifer as well as the
graph are nothing but the nodes in our
knowledge graph so as you can see for
representing this nodes in use in the
cipher query we have to surround the
node using the parenthesis so as you can
see in the round brackets we will
represent our nodes so now let's talk
about the variables and the node labels
so if you want to later refer our node
in the cipher query we can give it a
variable which is like a similar to
other programming language like Python
and you can represent the variable
inside the parenthesis itself so for
person you can mention like P or t for
think but this could be readable in the
real world because if your queries are a
bit complex and you have like a bigger
queries then putting a readable name
like for person you can directly call
your variable like a person so that will
be more readable than just providing P
so this is like a simple tip to write
Cipher queries so you can refer that
node in the subsequent commands in your
Cipher queries that is very simple and
if we talk about the node labels so if
you remember from the property graph
model we can also group our nodes in the
labels so let's say an example of like a
movie graph so in the movie data set we
will be having different kinds of notes
so some nodes will have like an
information about the movies so we can
provide a movie label and group all
those nodes together similarly we can
have like the nodes which represent
different properties belongs to some
actor so if the Keanu reuse is like a
node in our graph that belongs to the
actor label and similar goes to the
director as well as the person who watch
the movies as well as the ratings and so
on this could be anything so if you want
like you can have like different labels
in your graph so those could make sense
as well so in the movie recommendation
system having all these nodes would
really make sense and you can group that
together so a person could be like an
actor or a director so you can apply
multiple labels to that node and group
them together
so if we compare it to the relational
databases node labels are just like the
table names so if you have in the movie
data set in rdbms you will be having
like a movie table then you will be
having the actor table so to group all
those relevant records together similar
concept applies to the neo4j also in
which we will be having different kinds
of labels so that to group your relevant
data together okay so now we will talk
about the relationships in Cipher and
how we can represent it in a cyber query
so to add more connection and richness
to our graph we will introduce
relationships in our graph so earlier we
only had the notes in our graph but
those are not related to each other so
in this case we have brought the
different relationships and it has a
certain direction in our graph so as you
can see we got the likes is friends with
and the works for relationships so so
these are like the different
relationship types in our graph so this
also should be readable because at the
end of the day our graph should relate
to the English phrases because it is
represented as a simple English language
so as you can see here everyone should
be able to read that graph because we
have brought like the person label so we
already know that this particular person
for example Jennifer Phil likes some
neo4j technology so that there is a
relationship going from the person to
the technology so as you can see we can
relate our relationships and this makes
our graph more connected and also it
increases the performance while
traversing through the complex patterns
in our data and similar to the nodes as
well we can have like different
variables for our relationships so we
can assign like L variable to the likes
relationship then if variable to the
east friends relationship and W variable
for the works for relationship it
totally depends on you and you can refer
them in our subsequent steps in your
Cipher query so this is very helpful and
it is like similar to the other
programming language so once we jumped
in to writing our first Cipher queries
then you will understand how we can
utilize these variables so so far we
have talked about the most fundamental
components of our property Knowledge
Graph which is a nodes and relationship
but the last piece of this is the
relationship or a nodes properties that
we are going to see now so as you can
see these properties are nothing but a
key value pairs which will provide more
details and the additional data in our
nodes as well as the relationships so as
I already told you that properties could
be also in the nodes as well as in the
relationship so as you can see to
represent this in the cipher we are are
using the curly braces in our notes or
the relationships so you already know
that the node is represented between the
parenthesis and I forgot to told you
that the relationship is represented in
the square brackets so you have to
remember that that is like a
fundamentals of Cipher so as you can see
to represent any property which is in
the node we can directly give it in the
parenthesis of nodes so as you can see
we got the person node here in the
parenthesis and we have the curly
brackets in which we have the key value
pair so the key will be like the name
for person and like the property value
which is like a Jennifer so it
representing a person who has the
property name as Jennifer but we also
given a variable to our node which is p
so to refer this person in the
subsequent steps of your Cipher query
you can directly give it as P so
assigning variable is very important to
use that node in the further steps like
the wear condition to filter out your
nodes that is very important
and similarly to represent the property
in your relationship as a relationship
property so if you have like is friends
with and in this relationship we have
like a different property so since 2018
so which means that some person is
friends with since 2018 to another
person that is very simple English
language and everyone can like read that
using this so as you can see we got the
relationship is friends with in the
square brackets and we have the
directions as well so we can represent
this using the arrows so as you can see
we got the sense key and the 2018 value
in the curly braces and we have the Rel
Rel which represent this relationship
and Rel is a assigned variable for our
relationship so this is how you can
represent relationship or the node
properties in your Cipher query so so
far we have learned what is node what
are like relationships and how we can
represent them in the cipher query as
well as we have seen like how we can
represent different nodes and
relationship properties in your Cipher
so the next lecture will be we need to
discuss the cipher keywords which are
like very important like the select
Clause where Clause there are different
Cipher keywords present in neo4j so to
learn that you need to First understand
the basic fundamentals of the cipher so
in the next lecture we will talk about
and jump on to writing the cipher
queries from the beginner level to the
advanced level and we will see all the
syntax and like the different keywords
as well as like the complex stuff like
Loops as well as sub queries and all
that stuff in the sub segment lecture so
stay tuned And subscribe to the channel
and if you have any difficulties you can
let me know in the comments and we can
discuss further on it
thank you for watching this video
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