Agregasi dan Proyeksi
Pelajari cara menggunakan fungsi agregasi (misalnya, COUNT, SUM) dan memproyeksikan data ke dalam format khusus untuk analisis.
Agregasi dan Proyeksi adalah pelajaran Neo4j Graph Database Fundamentals gratis di CoddyKit. Ini adalah pelajaran 2 dari 4. Kamu bisa membaca pelajaran lengkapnya di bawah secara gratis — lalu praktikkan langsung di browser dengan editor kode bawaan dan tutor AI 24/7. Ini adalah bagian dari jalur belajar Neo4j Graph Database Fundamentals, dan progresmu tersinkronisasi di web dan aplikasi CoddyKit. Kursus Neo4j Graph Database Fundamentals mencakup 4 pelajaran total.
Bagian dari pelajaran ini belum diterjemahkan dan ditampilkan dalam bahasa Inggris.
Analyze Your Graph Data
Welcome to Aggregation and Projections! In graph databases, you often need to do more than just find data; you need to summarize it or shape it for analysis.
Aggregation means calculating a single result from multiple items, like counting all nodes or finding the average age. Projection is about selecting and formatting the data you want to see in your results.
Selecting Data with RETURN
The RETURN clause is how you specify exactly what data you want to see from your query. You can return nodes, relationships, or their specific properties. Let's add some example data first, then try a basic projection.
CREATE (p1:Person {name: 'Alice', age: 30})
CREATE (p2:Person {name: 'Bob', age: 25})
CREATE (p3:Person {name: 'Charlie', age: 30})
CREATE (m1:Movie {title: 'Inception', releaseYear: 2010})
CREATE (m2:Movie {title: 'Dunkirk', releaseYear: 2017})
CREATE (m3:Movie {title: 'Interstellar', releaseYear: 2014})
MATCH (p:Person)
RETURN p.name, p.ageCustomizing Output with AS
The default property names might not always be clear in your results. The AS keyword lets you rename returned items to make your query output more readable and descriptive. This is part of projection.
MATCH (m:Movie)
RETURN m.title AS FilmTitle, m.releaseYear AS YearReleasedCounting All Items with COUNT(*)
Aggregation functions help you summarize data. One of the most common is COUNT(*), which tells you the total number of items (nodes, relationships, or paths) found by your MATCH pattern.
MATCH (p:Person)
RETURN COUNT(*) AS TotalPeopleCountCounting Unique Values
What if you only want to count the unique values for a specific property? Use COUNT(DISTINCT variable.property). This is great for finding how many different ages, titles, or categories exist in your graph.
MATCH (p:Person)
RETURN COUNT(DISTINCT p.age) AS UniqueAgesCountSumming and Averaging Numbers
For numeric properties, you can calculate sums and averages. SUM() adds up all values, and AVG() computes their mean. These functions are very powerful for numerical analysis.
MATCH (p:Person)
RETURN SUM(p.age) AS TotalAgeSum, AVG(p.age) AS AverageAgeFinding Extremes with MIN/MAX
The MIN() and MAX() functions let you find the smallest and largest values for a property within your matched data. This is useful for identifying outliers or understanding data ranges.
MATCH (p:Person)
RETURN MIN(p.age) AS YoungestPersonAge, MAX(p.age) AS OldestPersonAgeGrouping into Lists with COLLECT
The COLLECT() function gathers all values of a specified property into a list. This is often used with grouping (which we'll cover later) but can also simply return all collected items in a list.
MATCH (p:Person)
RETURN COLLECT(p.name) AS AllPersonNamesStructuring Results with Maps
You can project complex, structured data using map projections. This allows you to create custom objects (maps) in your results, combining multiple properties and even calculated values into a single output column.
MATCH (p:Person)
RETURN {fullName: p.name, yearsOld: p.age, isAdult: p.age >= 18} AS PersonSummaryQuick Aggregation & Projection Check
Let's test your understanding of Cypher aggregation and projection. Choose all statements that correctly apply these concepts.
Recap: Aggregating & Projecting
Great job! You've learned how to summarize and shape your graph data using Cypher.
- Projections with
RETURNallow you to select specific data, rename it withAS, or create structured maps. - Aggregation functions like
COUNT(),SUM(),AVG(),MIN(),MAX(), andCOLLECT()help you analyze and summarize large datasets into meaningful insights.
These techniques are fundamental for extracting valuable information from your Neo4j graphs!
Pertanyaan yang Sering Diajukan
Apakah pelajaran “Agregasi dan Proyeksi” gratis?
Ya — teks lengkap “Agregasi dan Proyeksi” gratis dibaca di sini di web. Untuk praktiknya secara interaktif (editor kode bawaan dan tutor AI 24/7) dan buka sisa kursus Neo4j Graph Database Fundamentals, upgrade ke CoddyKit PRO. Kursus Neo4j Graph Database Fundamentals mencakup 4 pelajaran total.
Apa yang akan aku pelajari di “Agregasi dan Proyeksi”?
Pelajari cara menggunakan fungsi agregasi (misalnya, COUNT, SUM) dan memproyeksikan data ke dalam format khusus untuk analisis. Kamu berlatih Neo4j Graph Database Fundamentals dengan kode praktik yang langsung kamu jalankan di browser, dan tutor AI 24/7 menjawab pertanyaanmu saat kamu mengerjakan pelajaran ini.
Apakah aku perlu pengalaman untuk memulai Neo4j Graph Database Fundamentals?
Tidak diperlukan pengalaman sebelumnya. Neo4j Graph Database Fundamentals di CoddyKit dirancang untuk pemula hingga pelajar tingkat lanjut, jadi kamu bisa memulai di sini atau dari awal dan belajar sesuai kecepatan kamu sendiri. Ini adalah pelajaran 2 dari 4.
Berapa lama pelajaran “Agregasi dan Proyeksi” memakan waktu?
Sebagian besar pelajaran CoddyKit memakan waktu sekitar 5–10 menit. Setiap pelajaran ringkas dan interaktif, jadi kamu membuat kemajuan stabil dan melanjutkan dari tempat kamu tinggalkan di web dan aplikasi.
Bisakah aku menulis dan menjalankan kode dalam pelajaran Neo4j Graph Database Fundamentals ini?
Ya. Setiap pelajaran Neo4j Graph Database Fundamentals menyertakan editor kode bawaan, jadi kamu menulis dan menjalankan kode nyata langsung di browser dan mendapatkan umpan balik AI instan — tidak diperlukan penyiapan lokal.
Semua pelajaran dalam kursus ini
- Memfilter dan Mengurutkan Hasil
- Agregasi dan Proyeksi
- Memperbarui dan Menghapus Data Graf
- Menggabungkan Kueri dengan WITH dan UNION