How do queries work in Cloud Firestore? | Get to know Cloud Firestore #2

Summary

This video provides an in-depth overview of querying in Cloud Firestore, highlighting its differences from SQL databases and emphasizing its speed and efficiency. Todd explains how to perform various queries, including collection group queries and the importance of composite indexes for handling complex searches. He discusses limitations, such as the inability to perform joins or mixed-type queries, while showcasing the benefits of shallow results and automated indexing. Ultimately, the video equips viewers with essential knowledge to leverage Cloud Firestore's querying capabilities effectively.

Takeaways

• 😀 Cloud Firestore querying is limited to specific collections or sub-collections, allowing for targeted searches.
• 😀 Collection group queries enable searching across multiple collections with the same name, enhancing flexibility.
• 😀 Query results are shallow, meaning only the matching documents are returned, not their associated sub-collections.
• 😀 Performance is optimized because queries run in proportional time to the number of results returned, not the total documents searched.
• 😀 Each field in a document is automatically indexed, which facilitates fast lookups using binary search algorithms.
• 😀 Composite indexes are automatically maintained for field combinations, allowing for efficient multi-field queries.
• 😀 Full-text searches, OR queries, and 'not equal to' queries are not supported directly and require workarounds.
• 😀 Mixing data types in indexed fields can complicate searches and lead to inefficiencies.
• 😀 The order of fields in composite indexes is crucial, especially when combining equality and inequality queries.
• 😀 Developers can create composite indexes directly through the Firebase console or via links provided in error messages when a needed index is missing.

Q & A

What is the primary difference between a database and a messy room, according to Todd?

The primary difference is that a database is designed to not only store data but also allow for efficient retrieval, unlike a messy room where finding items can be difficult.

How do NoSQL databases differ from SQL databases in terms of querying capabilities?

NoSQL databases, like Cloud Firestore, have different querying capabilities that often allow for more flexibility, especially in how data is structured and accessed compared to traditional SQL databases.

What are collection group queries in Cloud Firestore?

Collection group queries allow you to perform searches across multiple sub-collections that share the same name within the Firestore database.

What is the limit on the number of collection group queries that can be created in Cloud Firestore?

You are limited to about 200 collection group queries in Cloud Firestore.

Why are results in Cloud Firestore considered 'shallow'?

Results are considered shallow because queries return only the documents from the queried collection and do not include data from any associated sub-collections.

What happens when you perform a query based on a calculation in Firestore?

You cannot query based on a calculation directly; instead, you would need to create a separate field that holds the calculated value and keep it updated.

How does Cloud Firestore optimize query performance?

Cloud Firestore optimizes query performance by automatically creating indexes for every field in a document, allowing for quick searches even as the number of documents increases.

What are composite indexes and why are they important?

Composite indexes are used to efficiently query multiple fields at once. They simplify complex queries and improve performance by maintaining the necessary sorting at the index level.

What is the recommended approach to creating composite indexes in Firestore?

The recommended approach is to trigger an error while running a query that requires a composite index, which will provide a direct link to create the needed index in the Firebase console.

Can you mix different data types in the same field when indexing, and what is the implication?

While it is technically possible to mix data types in a field, it is discouraged because it results in multiple indexes that require separate searches, complicating queries and reducing efficiency.