How to Query Fields That Don’t Exist in Firestore

As developers working with the Firestore database, we often come across situations where we need to query documents that don’t have a certain field. It should be easy, right? Unfortunately, however, this seemingly simple task is more challenging than expected. In this article, we’ll explore why querying non-existent fields in Firestore is a problem and discuss some possible solutions.

Challenge: Firestore’s Indexing Mechanism

Firestore’s query power is built into its indexing system. As Doug Stevenson, a former Firebase team member, put it succinctly:

“You can’t ask for something that isn’t in Firestore. The field needs to exist for the Firestore directory to know about. “

– Doug Stevenson

For example, if you try to make the following Firestore query call in Node.js – where db your initialized Firestore connection:

const querySnapShot = await db.collection("users").where("age", "==", null).get();
querySnapShot.forEach(doc => console.log(doc.data());

No results will be returned.

This key feature of Firestore’s architecture means that traditional methods of querying missing fields, such as where("field", "==", null) it just won’t work.

Why Can’t We Query Missing Fields?

The reason lies in the way Firestore handles its indexes:

1. All Firestore queries are index dependent. This is what makes asking so fast and why when you try to use i where query in the new location you need to create an index.
2. A document is only inserted into a field index if that field exists in a Firestore document. Ie how can you identify something that doesn’t exist? You can’t.
3. If a document does not have a value for a particular field, it will not exist in the index for that field.

This means that there is no direct way to query documents that do not have a specific field, since those documents are not represented in the correct index. So, if you use the where("field", "==", null) nothing comes back.

You might also ask, “Well, in MongoDB you can easily query for missing fields, so why not do Firestore?” Of course you can do a query like db.mycollection.find({“ages” : {“$exists” : false } }). However, you cannot perform a MongoDB index search when querying with $"exists": false making the query slow and inefficient.

Workarounds and solutions

Despite this limitation, there are several methods we can use to “query” missing fields. Unfortunately each solution has a trade-off, as we’ll see below.

1. Download All Documents and Filter Client or Server Side

If you’re working with small batches, you can download all the documents and sort them in your application code. This is currently the most straightforward way to find documents without a specific field:

const getAllDocsWithoutField = async (collectionName, fieldName) => {
  const snapshot = await db.collection(collectionName).get();

  const docsWithoutField = snapshot.docs.filter(doc => {
    const data = doc.data();
    return !(fieldName in data);
  });

  return docsWithoutField;
};

// Example Usage
const docsWithoutAge = await getAllDocsWithoutField('users', 'age');

Advantages of this method::

1. Simplicity: This method is easy to use and understand.
2. Flexibility: You can easily change the filter logic to handle complex cases or multiple fields.
3. No Data Model Changes: Does not require changes to your existing data structure.
4. Accurate Results: This method ensures to find all documents except the specified field.

Disadvantages of this method:

1. Inefficiency: This method requires downloading all the documents in the collection, which can be slow and consume resources for large collections.
2. Costs: Firestore costs for learning activities. In this way, you read all the documents in the collection, which can be called quickly. Starting in 2024, Google Cloud charges $0.031 per 100,000 documents read in most regions.
3. Bandwidth: Downloading all documents consumes more bandwidth, which can be a concern for mobile applications or in regions with limited internet connection. We generally recommend making these calls on the server side for large applications.
4. Firestore Query Limits: Firestore has a limit on the amount of data that can be returned in a single query. The current limit is 1 MB. With large collections, you may reach this limit before retrieving all documents.
5. Working: Since filtering occurs on the client side, the performance of the filtering function depends on the client’s hardware, which may lead to slower performance on less powerful devices. Also, you might consider doing this server side.

2. Set the None field to Inactive

If querying documents without a specific field is a common requirement in your application, consider editing the field in it null. For example:

{
  name: "John Doe",
  age: 30
}
{
  name: "Jane Smith",
  age: null
}

This allows you to ask directly:

const snapshot = await db.collection('users')
  .where('age', '==', null)
  .get();

Advantages of this method:

1. Good performance: This query can use Firestore indexes, which makes it much faster and more cost-effective than downloading all the documents.
2. Scalability: This method works well even for very large clusters.
3. Cost effective: You only get the documents you need, reducing read performance and bandwidth usage.

Disadvantages of this method:

1. Maintenance overhead: You need to confirm null field is set explicitly whenever you add or update documents, and you update existing documents with null field if it does not currently exist. This can be a problem depending on how you designed your system.
2. Data Confusion: Stores an additional field, possibly for multiple documents, which slightly increases storage costs, but not much.

Impacts and Best Practices

Not being able to directly query fields that don’t exist in Firestore has several implications for application design and data modeling:

1. Data Model Considerations: When designing your Firestore data model, consider whether you will need to query for missing fields. If so, plan to merge null field from the beginning.
2. Application Logic: Be prepared to handle out-of-place fields in your application code.
3. Operational Planning: For large collections, use pagination or limit the range of queries to avoid performance issues when using client-side filtering. You can use the limit task to achieve this.
4. Cost Management: Be aware of the potential costs associated with reading entire collections. Consider using caching techniques – perhaps in Redis or Firestore Bundles.

There is no Perfect Solution

Querying fields that do not exist in Firestore has been a challenge due to the structure of the database. Although there is no perfect solution, the methods described above offer ways to deal with this limitation. Choosing between client- or server-side filtering or using a virtual platform depends on your use case, the size of your data, update frequency, and performance requirements. If you are starting a new collection, the second options may be the best fit.

As Firestore continues to evolve, it’s worth keeping an eye on new features or query capabilities that might address this limitation in the future – while the ability to query non-existent platforms like MongoDB has been requested for years, we hope it will. released.

Bonus

A nifty Firestore function for the query orderBywhich only returns documents with that field. For example, .orderBy("age") will return documents only with age field. Although this is not useful for querying missing fields, if it can be useful for finding specific documents and not returning the entire collection.

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