拆分

說明

為陣列中的每個元素生成新文件。

新文件會包含輸入內容的所有欄位，以及陣列中的不同元素。陣列元素會儲存至指定的 alias，可能會覆寫任何具有相同欄位名稱的現有值。

您可以視需要指定 index_field 引數。如果存在，輸出文件會包含來源陣列中元素的索引 (從零算起)。

這個階段的行為與許多 SQL 系統中的 CROSS JOIN UNNEST(...) 類似。

範例

Node.js

const userScore = await db.pipeline()
    .collection("/users")
    .unnest(field("scores").as("userScore"), /* index_field= */ "attempt")
    .execute();

行為

別名和索引欄位

如果輸入文件中已有欄位，alias 和選用的 index_field 會覆寫原始欄位。如果未提供 index_field，輸出文件就不會包含這個欄位。

舉例來說，如果集合如下：

Node.js

await db.collection("users").add({name: "foo", scores: [5, 4], userScore: 0});
await db.collection("users").add({name: "bar", scores: [1, 3], attempt: 5});

unnest 階段可用於擷取每位使用者的個別分數。

Node.js

const userScore = await db.pipeline()
    .collection("/users")
    .unnest(field("scores").as("userScore"), /* index_field= */ "attempt")
    .execute();

在本例中，userScore 和 attempt 都會遭到覆寫。

  {name: "foo", scores: [5, 4], userScore: 5, attempt: 0}
  {name: "foo", scores: [5, 4], userScore: 4, attempt: 1}
  {name: "bar", scores: [1, 3], userScore: 1, attempt: 0}
  {name: "bar", scores: [1, 3], userScore: 3, attempt: 1}

其他範例

Swift
let results = try await db.pipeline()
  .database()
  .unnest(Field("arrayField").as("unnestedArrayField"), indexField: "index")
  .execute()

Kotlin

val results = db.pipeline()
    .database()
    .unnest(field("arrayField").alias("unnestedArrayField"), UnnestOptions().withIndexField("index"))
    .execute()

Java

Task<Pipeline.Snapshot> results = db.pipeline()
    .database()
    .unnest(field("arrayField").alias("unnestedArrayField"), new UnnestOptions().withIndexField("index"))
    .execute();
Python
from google.cloud.firestore_v1.pipeline_expressions import Field
from google.cloud.firestore_v1.pipeline_stages import UnnestOptions

results = (
    client.pipeline()
    .database()
    .unnest(
        Field.of("arrayField").as_("unnestedArrayField"),
        options=UnnestOptions(index_field="index"),
    )
    .execute()
)
Java
Pipeline.Snapshot results =
    firestore
        .pipeline()
        .database()
        .unnest("arrayField", "unnestedArrayField", new UnnestOptions().withIndexField("index"))
        .execute()
        .get();
Go
snapshot := client.Pipeline().
	Database().
	UnnestWithAlias("arrayField", "unnestedArrayField", firestore.WithUnnestIndexField("index")).
	Execute(ctx)

非陣列值

如果輸入運算式評估結果為非陣列值，則這個階段會傳回輸入文件，並將 index_field 設為 NULL (如有指定)。

舉例來說，如果集合如下：

Node.js

await db.collection("users").add({name: "foo", scores: 1});
await db.collection("users").add({name: "bar", scores: null});
await db.collection("users").add({name: "qux", scores: {backupScores: 1}});

unnest 階段可用於擷取每位使用者的個別分數。

Node.js

const userScore = await db.pipeline()
    .collection("/users")
    .unnest(field("scores").as("userScore"), /* index_field= */ "attempt")
    .execute();

這會產生下列文件，且 attempt 設為 NULL。

  { name: "foo", scores: 1, attempt: null }
  { name: "bar", scores: null, attempt: null }
  { name: "qux", scores: { backupScores: 1 }, attempt: null }

空陣列值

如果輸入運算式評估結果為空陣列，系統就不會傳回該輸入文件的任何文件。

舉例來說，如果集合如下：

Node.js

await db.collection("users").add({name: "foo", scores: [5, 4]});
await db.collection("users").add({name: "bar", scores: []});

unnest 階段可用於擷取每位使用者的個別分數。

Node.js

const userScore = await db.pipeline()
    .collection("/users")
    .unnest(field("scores").as("userScore"), /* index_field= */ "attempt")
    .execute();

這會產生下列文件，且輸出內容中缺少使用者 bar。

  {name: "foo", scores: [5, 4], userScore: 5, attempt: 0}
  {name: "foo", scores: [5, 4], userScore: 4, attempt: 1}

如要一併傳回含有空陣列的文件，可以將未巢狀化的值包裝在陣列中。例如：

Node.js

const userScore = await db.pipeline()
    .collection("/users")
    .unnest(
      conditional(
        equal(field("scores"), []),
        array([field("scores")]),
        field("scores")
      ).as("userScore"),
    /* index_field= */ "attempt")
    .execute();

現在會傳回使用者 bar 的文件。

  {name: "foo", scores: [5, 4], userScore: 5, attempt: 0}
  {name: "foo", scores: [5, 4], userScore: 4, attempt: 1}
  {name: "bar", scores: [], userScore: [], attempt: 0}

其他範例

Node.js
    // Input
    // { identifier : 1, neighbors: [ "Alice", "Cathy" ] }
    // { identifier : 2, neighbors: []                   }
    // { identifier : 3, neighbors: "Bob"                }

    const results = await db.pipeline()
      .database()
      .unnest(Field.of("neighbors"), "unnestedNeighbors", "index")
      .execute();

    // Output
    // { identifier: 1, neighbors: [ "Alice", "Cathy" ], unnestedNeighbors: "Alice", index: 0 }
    // { identifier: 1, neighbors: [ "Alice", "Cathy" ], unnestedNeighbors: "Cathy", index: 1 }
    // { identifier: 3, neighbors: "Bob", index: null}
Swift
// Input
// { identifier : 1, neighbors: [ "Alice", "Cathy" ] }
// { identifier : 2, neighbors: []                   }
// { identifier : 3, neighbors: "Bob"                }

let results = try await db.pipeline()
  .database()
  .unnest(Field("neighbors").as("unnestedNeighbors"), indexField: "index")
  .execute()

// Output
// { identifier: 1, neighbors: [ "Alice", "Cathy" ], unnestedNeighbors: "Alice", index: 0 }
// { identifier: 1, neighbors: [ "Alice", "Cathy" ], unnestedNeighbors: "Cathy", index: 1 }
// { identifier: 3, neighbors: "Bob", index: null}

Kotlin

// Input
// { identifier : 1, neighbors: [ "Alice", "Cathy" ] }
// { identifier : 2, neighbors: []                   }
// { identifier : 3, neighbors: "Bob"                }

val results = db.pipeline()
    .database()
    .unnest(field("neighbors").alias("unnestedNeighbors"), UnnestOptions().withIndexField("index"))
    .execute()

// Output
// { identifier: 1, neighbors: [ "Alice", "Cathy" ], unnestedNeighbors: "Alice", index: 0 }
// { identifier: 1, neighbors: [ "Alice", "Cathy" ], unnestedNeighbors: "Cathy", index: 1 }
// { identifier: 3, neighbors: "Bob", index: null}

Java

// Input
// { identifier : 1, neighbors: [ "Alice", "Cathy" ] }
// { identifier : 2, neighbors: []                   }
// { identifier : 3, neighbors: "Bob"                }

Task<Pipeline.Snapshot> results = db.pipeline()
    .database()
    .unnest(field("neighbors").alias("unnestedNeighbors"), new UnnestOptions().withIndexField("index"))
    .execute();

// Output
// { identifier: 1, neighbors: [ "Alice", "Cathy" ], unnestedNeighbors: "Alice", index: 0 }
// { identifier: 1, neighbors: [ "Alice", "Cathy" ], unnestedNeighbors: "Cathy", index: 1 }
// { identifier: 3, neighbors: "Bob", index: null}
Python
from google.cloud.firestore_v1.pipeline_expressions import Field
from google.cloud.firestore_v1.pipeline_stages import UnnestOptions

# Input
# { "identifier" : 1, "neighbors": [ "Alice", "Cathy" ] }
# { "identifier" : 2, "neighbors": []                   }
# { "identifier" : 3, "neighbors": "Bob"                }

results = (
    client.pipeline()
    .database()
    .unnest(
        Field.of("neighbors").as_("unnestedNeighbors"),
        options=UnnestOptions(index_field="index"),
    )
    .execute()
)

# Output
# { "identifier": 1, "neighbors": [ "Alice", "Cathy" ],
#   "unnestedNeighbors": "Alice", "index": 0 }
# { "identifier": 1, "neighbors": [ "Alice", "Cathy" ],
#   "unnestedNeighbors": "Cathy", "index": 1 }
# { "identifier": 3, "neighbors": "Bob", "index": null}
Java
// Input
// { "identifier" : 1, "neighbors": [ "Alice", "Cathy" ] }
// { "identifier" : 2, "neighbors": []                   }
// { "identifier" : 3, "neighbors": "Bob"                }

Pipeline.Snapshot results =
    firestore
        .pipeline()
        .database()
        .unnest("neighbors", "unnestedNeighbors", new UnnestOptions().withIndexField("index"))
        .execute()
        .get();

// Output
// { "identifier": 1, "neighbors": [ "Alice", "Cathy" ],
//   "unnestedNeighbors": "Alice", "index": 0 }
// { "identifier": 1, "neighbors": [ "Alice", "Cathy" ],
//   "unnestedNeighbors": "Cathy", "index": 1 }
// { "identifier": 3, "neighbors": "Bob", "index": null}
Go
// Input
// { "identifier" : 1, "neighbors": [ "Alice", "Cathy" ] }
// { "identifier" : 2, "neighbors": []                   }
// { "identifier" : 3, "neighbors": "Bob"                }

results, err := client.Pipeline().
	Database().
	UnnestWithAlias("neighbors", "unnestedNeighbors", firestore.WithUnnestIndexField("index")).
	Execute(ctx).Results().GetAll()
if err != nil {
	fmt.Fprintf(w, "GetAll failed: %v", err)
	return err
}

// Output
// { "identifier": 1, "neighbors": [ "Alice", "Cathy" ],
//   "unnestedNeighbors": "Alice", "index": 0 }
// { "identifier": 1, "neighbors": [ "Alice", "Cathy" ],
//   "unnestedNeighbors": "Cathy", "index": 1 }
// { "identifier": 3, "neighbors": "Bob", "index": nil}

巢狀 Unnest

如果運算式評估結果為巢狀陣列，則必須使用多個 unnest(...) 階段，才能將每個巢狀層級攤平。

舉例來說，如果集合如下：

Node.js

await db.collection("users").add({name: "foo", record: [{scores: [5, 4], avg: 4.5}, {scores: [1, 3], old_avg: 2}]});

unnest(...) 階段可依序用來擷取最內層的陣列。

Node.js

const userScore = await db.pipeline()
    .collection("/users")
    .unnest(field("record").as("record"))
    .unnest(field("record.scores").as("userScore"), /* index_field= */ "attempt")
    .execute();

這會產生下列文件：

  { name: "foo", record: [{ scores: [5, 4], avg: 4.5 }], userScore: 5, attempt: 0 }
  { name: "foo", record: [{ scores: [5, 4], avg: 4.5 }], userScore: 4, attempt: 1 }
  { name: "foo", record: [{ scores: [1, 3], avg: 2 }], userScore: 1, attempt: 0 }
  { name: "foo", record: [{ scores: [1, 3], avg: 2 }], userScore: 3, attempt: 1 }