Sample

Description

Returns a non-deterministic sample from the results of the previous stage.

There are two supported modes:

  • DOCUMENTS mode allows for sampling a set number of documents
    • This mode is similar to GoogleSQL.RESERVOIR in that it outputs a sample of size n, where any sample of size n is equally possible.
  • PERCENT mode allows for sampling a percentage of documents
    • This mode is similar to GoogleSQL.BERNOULLI in that each document is independently selected with an equal percent probability. This results in #documents * percent / 100 documents being returned on average.

Syntax

Node.js

  const sampled = await db.pipeline()
    .database()
    .sample(50)
    .execute();

  const sampled = await db.pipeline()
    .database()
    .sample({ percent: 0.5 })
    .execute();

Behavior

Documents Mode

Documents mode retrieves a specified number of documents in a random order. The specified number must be a non-negative INT64 value.

For example, for the following collection:

Node.js

await db.collection('cities').doc('SF').set({name: 'San Francsico', state: 'California'});
await db.collection('cities').doc('NYC').set({name: 'New York City', state: 'New York'});
await db.collection('cities').doc('CHI').set({name: 'Chicago', state: 'Illinois'});

The sample stage in document mode can be used to retrieve a non-deterministic subset of results from this collection.

Node.js

const sampled = await db.pipeline()
    .collection("/cities")
    .sample(1)
    .execute();

In this example, only 1 document at random would be returned at random.

  {name: 'New York City', state: 'New York'}

If the supplied number is greater than the total number of documents returned, all documents are returned in a random order.

Node.js

const sampled = await db.pipeline()
    .collection("/cities")
    .sample(5)
    .execute();

This will result in the following documents:

  {name: 'New York City', state: 'New York'}
  {name: 'Chicago', state: 'Illinois'}
  {name: 'San Francisco', state: 'California'}

Client examples

Web

let results;

// Get a sample of 100 documents in a database
results = await execute(db.pipeline()
  .database()
  .sample(100)
);

// Randomly shuffle a list of 3 documents
results = await execute(db.pipeline()
  .documents([
    doc(db, "cities", "SF"),
    doc(db, "cities", "NY"),
    doc(db, "cities", "DC"),
  ])
  .sample(3)
);
test.firestore.js
Swift
var results: Pipeline.Snapshot

// Get a sample of 100 documents in a database
results = try await db.pipeline()
  .database()
  .sample(count: 100)
  .execute()

// Randomly shuffle a list of 3 documents
results = try await db.pipeline()
  .documents([
    db.collection("cities").document("SF"),
    db.collection("cities").document("NY"),
    db.collection("cities").document("DC"),
  ])
  .sample(count: 3)
  .execute()
PipelineSnippets.swift

Kotlin

var results: Task<Pipeline.Snapshot>

// Get a sample of 100 documents in a database
results = db.pipeline()
    .database()
    .sample(100)
    .execute()

// Randomly shuffle a list of 3 documents
results = db.pipeline()
    .documents(
        db.collection("cities").document("SF"),
        db.collection("cities").document("NY"),
        db.collection("cities").document("DC")
    )
    .sample(3)
    .execute()
DocSnippets.kt

Java

Task<Pipeline.Snapshot> results;

// Get a sample of 100 documents in a database
results = db.pipeline()
    .database()
    .sample(100)
    .execute();

// Randomly shuffle a list of 3 documents
results = db.pipeline()
    .documents(
        db.collection("cities").document("SF"),
        db.collection("cities").document("NY"),
        db.collection("cities").document("DC")
    )
    .sample(3)
    .execute();
DocSnippets.java
Python
# Get a sample of 100 documents in a database
results = client.pipeline().database().sample(100).execute()

# Randomly shuffle a list of 3 documents
results = (
    client.pipeline()
    .documents(
        client.collection("cities").document("SF"),
        client.collection("cities").document("NY"),
        client.collection("cities").document("DC"),
    )
    .sample(3)
    .execute()
)
firestore_pipelines.py
Java
// Get a sample of 100 documents in a database
Pipeline.Snapshot results1 = firestore.pipeline().database().sample(100).execute().get();

// Randomly shuffle a list of 3 documents
Pipeline.Snapshot results2 =
    firestore
        .pipeline()
        .documents(
            firestore.collection("cities").document("SF"),
            firestore.collection("cities").document("NY"),
            firestore.collection("cities").document("DC"))
        .sample(3)
        .execute()
        .get();
PipelineSnippets.java

Percent Mode

In percent mode, each document has a specified percent chance of being returned. Unlike documents mode, the order here is not random and instead preserves the pre-existing document order. This percent input must be a double value between 0.0 and 1.0.

Since each document is independently selected, the output is non-deterministic and on average, #documents * percent / 100 documents will be returned.

For example, for the following collection:

Node.js

await db.collection('cities').doc('SF').set({name: 'San Francsico', state: 'California'});
await db.collection('cities').doc('NYC').set({name: 'New York City', state: 'New York'});
await db.collection('cities').doc('CHI').set({name: 'Chicago', state: 'Illinois'});
await db.collection('cities').doc('ATL').set({name: 'Atlanta', state: 'Georgia'});

The sample stage in percent mode can be used to retrieve (on average) 50% of the documents from the collection stage.

Node.js

  const sampled = await db.pipeline()
    .collection("/cities")
    .sample({ percent: 0.5 })
    .execute();

This will result in a non-deterministic sample of (on average) 50% of documents from the cities collection. The following is one possible output.

  {name: 'New York City', state: 'New York'}
  {name: 'Chicago', state: 'Illinois'}

In percent mode, because each document has the same probability of being selected, it is possible for no documents or all documents to be returned.

Client examples

Web

// Get a sample of on average 50% of the documents in the database
const results = await execute(db.pipeline()
  .database()
  .sample({ percentage: 0.5 })
);
test.firestore.js
Swift
// Get a sample of on average 50% of the documents in the database
let results = try await db.pipeline()
  .database()
  .sample(percentage: 0.5)
  .execute()
PipelineSnippets.swift

Kotlin

// Get a sample of on average 50% of the documents in the database
val results = db.pipeline()
    .database()
    .sample(SampleStage.withPercentage(0.5))
    .execute()
DocSnippets.kt

Java

// Get a sample of on average 50% of the documents in the database
Task<Pipeline.Snapshot> results = db.pipeline()
    .database()
    .sample(SampleStage.withPercentage(0.5))
    .execute();
DocSnippets.java
Python
from google.cloud.firestore_v1.pipeline_stages import SampleOptions

# Get a sample of on average 50% of the documents in the database
results = (
    client.pipeline().database().sample(SampleOptions.percentage(0.5)).execute()
)
firestore_pipelines.py
Java
// Get a sample of on average 50% of the documents in the database
Pipeline.Snapshot results =
    firestore.pipeline().database().sample(Sample.withPercentage(0.5)).execute().get();
PipelineSnippets.java