Week 10 - Cypher Queries

This week's lab focuses on writing and understanding Cypher queries. Let's use the database that we created last week (week 9 lab sheet) as the example.

1. READ

Write queries that find each of the following:

  1. All nodes in the database.

MATCH (n) RETURN n

  1. All products in the database.

MATCH (n:Product) RETURN n

  1. Up to 5 products in the database.

MATCH (n:Product) RETURN n LIMIT 5

  1. All products whose prices are greater than 20. We will talk about toFloat() in Section 2. UPDATE.

MATCH (n:Product)
WHERE toFloat(n.purchasePrice) > 20
RETURN n

  1. All sales which contain a product with the brand "Mega".

MATCH (s:Sale)-[:CONTAINS]->(p:Product {brand: "Mega"})
RETURN s

Alternatively, If you don't need to reference the "Product" node itself, you can simplify the query by removing "p".

MATCH (s:Sale)-[:CONTAINS]->(:Product {brand: "Mega"})
RETURN s

  1. All shops that have sales of a product with the brand "Mega".

MATCH (s:Shop)<-[:SOLD_IN]-(:Sale)-[:CONTAINS]->(:Product{brand:"Mega"})
RETURN s

  1. Same query as 6, but return the path.

MATCH p=(s:Shop)<-[:SOLD_IN]-(:Sale)-[:CONTAINS]->(:Product{brand:"Mega"})
RETURN p

  1. In this example dataset, our relationships don't have properties. However, what if we need to query based on a property of a relationship? Let's assume there's a "year" property on the "SOLD_IN" relationship. Here's how you can modify the query to include this relationship property:

MATCH (p:Product {brand: "Mega"})-[:CONTAINS]-(s:Sale)-[:SOLD_IN]-(sh:Shop)
WHERE s.date STARTS WITH '2021'
RETURN DISTINCT sh

If there's a "year" property on the "SOLD_IN" relationship, the query should be:

MATCH (p:Product {brand: "Mega"})-[:CONTAINS]->(s:Sale)-[r:SOLD_IN {year: 2021}]->(sh:Shop)
RETURN DISTINCT sh

The output of the above query should be (no changes, no records) as there is no "year" property on the "SOLD_IN" relationship.

Your turn: What does Query 8 mean?

  1. Find the path with a length of 4 from the product with ID "TAB_1" to the product with ID "TSH_9":

MATCH p=(:Product {productID: "TAB_1"})-[*4]-(:Product {productID: "TSH_9"})
RETURN p

For more information on path queries: https://neo4j.com/developer-blog/the-power-of-the-path-1/

NOTE: All the variables used in the queries, such as "s", "n", and "p", are self-defined. You can replace these variable names with any valid variable name of your choice.

2. UPDATE

Sometimes, records such as product price might need updating. Instead of uploading a new CSV file, we can write queries to update the information directly in the database.

  1. Updates a product's price to a different price.

Check the current price of the product with ID: "BED_3" and its type:

MATCH (p:Product {productID: "BED_3"})
RETURN p.purchasePrice
Figure 1: checking property types from RETURN clause

Alternatively, you can return the node and hover over the property to see its type:

Figure 2: checking property types from nodes

You can see that the purchasePrice is stored as a string. This is because when we created nodes from a CSV file (see Week9), we did not specify the price as a float, so Neo4j automatically treated every variable as a string.

Two methods to change the type:

Method 1: Changing the type when creating the database from a CSV file, you can use conversion functions such as toInteger(), toFloat(), toString(), toBoolean(). You can learn more about these functions in the Neo4j documentation: Scalar functions

For example:

LOAD CSV WITH HEADERS FROM 'file:///products.csv' AS row
CREATE (d:Product {
    productID: row.`Product`,
    category: row.Category,
    subcategory: row.`Sub category`,
    productSize: row.Size,
    purchasePrice: toFloat(row.`Purchase price`),
    color: row.Color,
    brand:row.Brand
})

In this example, toFloat() is used to convert the purchasePrice property from a string to a float during node creation.

Method 2: Updating the type aftering creating:

MATCH (p:Product)
SET p.purchasePrice = toFloat(p.purchasePrice)

Your turn: compare Figure 1 with Figure 3. What's the difference between their results?

Figure 3: checking property types from RETURN clause (after updated)

Now, let's update the price:

MATCH (p:Product {productID: "BED_3"})
SET p.purchasePrice = 125.0

Your turn:

3. DELETE

  1. Deletes a specific shop in the database

MATCH (n:Shop {shopID: "shop_14"})
DETACH DELETE n

  1. Deletes a relationship between a specific Shop and a specific Sale

MATCH p=(n:Sale{saleID: "S000001480"})-[r:SOLD_IN]->(s:Shop{shopID:"shop_0"})
DELETE r

Your turn:

  1. What is the difference between "DELETE" and "DETACH DELETE": https://neo4j.com/docs/cypher-manual/current/clauses/delete/

  2. Delete all nodes and relationships in the database.

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