Upsert Block

The upsert block allows performing queries and mutations in a single request. The upsert block contains one query block and one or more than one mutation blocks. Variables defined in the query block can be used in the mutation blocks using the uid and val function.

In general, the structure of the upsert block is as follows:

upsert {
  query <query block>
  [fragment <fragment block>]
  mutation <mutation block 1>
  [mutation <mutation block 2>]
  ...
}

Execution of an upsert block also returns the response of the query executed on the state of the database before mutation was executed. To get the latest result, we should commit the mutation and execute another query.

uid Function

The uid function allows extracting UIDs from variables defined in the query block. There are two possible outcomes based on the results of executing the query block:

• If the variable is empty i.e. no node matched the query, the uid function returns a new UID in case of a set operation and is thus treated similar to a blank node. On the other hand, for delete/del operation, it returns no UID, and thus the operation becomes a no-op and is silently ignored. A blank node gets the same UID across all the mutation blocks.
• If the variable stores one or more than one UIDs, the uid function returns all the UIDs stored in the variable. In this case, the operation is performed on all the UIDs returned, one at a time.

val Function

The val function allows extracting values from value variables. Value variables store a mapping from UIDs to their corresponding values. Hence, val(v) is replaced by the value stored in the mapping for the UID (Subject) in the N-Quad. If the variable v has no value for a given UID, the mutation is silently ignored. The val function can be used with the result of aggregate variables as well, in which case, all the UIDs in the mutation would be updated with the aggregate value.

Example of uid Function

Consider an example with the following schema:

curl localhost:8080/alter -X POST -d $'
  name: string @index(term) .
  email: string @index(exact, trigram) @upsert .
  age: int @index(int) .' | jq

Now, let’s say we want to create a new user with email and name information. We also want to make sure that one email has exactly one corresponding user in the database. To achieve this, we need to first query whether a user exists in the database with the given email. If a user exists, we use its UID to update the name information. If the user doesn’t exist, we create a new user and update the email and name information.

We can do this using the upsert block as follows:

curl -H "Content-Type: application/rdf" -X POST localhost:8080/mutate?commitNow=true -d $'
upsert {
  query {
    q(func: eq(email, "user@company1.io")) {
      v as uid
      name
    }
  }

  mutation {
    set {
      uid(v) <name> "first last" .
      uid(v) <email> "user@company1.io" .
    }
  }
}' | jq

Result:

{
  "data": {
    "q": [],
    "code": "Success",
    "message": "Done",
    "uids": {
      "uid(v)": "0x1"
    }
  },
  "extensions": {...}
}

The query part of the upsert block stores the UID of the user with the provided email in the variable v. The mutation part then extracts the UID from variable v, and stores the name and email information in the database. If the user exists, the information is updated. If the user doesn’t exist, uid(v) is treated as a blank node and a new user is created as explained above.

If we run the same mutation again, the data would just be overwritten, and no new uid is created. Note that the uids map is empty in the result when the mutation is executed again and the data map (key q) contains the uid that was created in the previous upsert.

{
  "data": {
    "q": [
      {
        "uid": "0x1",
        "name": "first last"
      }
    ],
    "code": "Success",
    "message": "Done",
    "uids": {}
  },
  "extensions": {...}
}

We can achieve the same result using json dataset as follows:

curl -H "Content-Type: application/json" -X POST localhost:8080/mutate?commitNow=true -d '
{
  "query": "{ q(func: eq(email, \"user@company1.io\")) {v as uid, name} }",
  "set": {
    "uid": "uid(v)",
    "name": "first last",
    "email": "user@company1.io"
  }
}' | jq

Now, we want to add the age information for the same user having the same email user@company1.io. We can use the upsert block to do the same as follows:

curl -H "Content-Type: application/rdf" -X POST localhost:8080/mutate?commitNow=true -d $'
upsert {
  query {
    q(func: eq(email, "user@company1.io")) {
      v as uid
    }
  }

  mutation {
    set {
      uid(v) <age> "28" .
    }
  }
}' | jq

Result:

{
  "data": {
    "q": [
      {
        "uid": "0x1"
      }
    ],
    "code": "Success",
    "message": "Done",
    "uids": {}
  },
  "extensions": {...}
}

Here, the query block queries for a user with email as user@company1.io. It stores the uid of the user in variable v. The mutation block then updates the age of the user by extracting the uid from the variable v using uid function.

We can achieve the same result using json dataset as follows:

curl -H "Content-Type: application/json" -X POST localhost:8080/mutate?commitNow=true -d $'
{
  "query": "{ q(func: eq(email, \\"user@company1.io\\")) {v as uid} }",
  "set":{
    "uid": "uid(v)",
    "age": "28"
  }
}' | jq

If we want to execute the mutation only when the user exists, we could use Conditional Upsert.

Example of val Function

Let’s say we want to migrate the predicate age to other. We can do this using the following mutation:

curl -H "Content-Type: application/rdf" -X POST localhost:8080/mutate?commitNow=true -d $'
upsert {
  query {
    v as var(func: has(age)) {
      a as age
    }
  }

  mutation {
    # we copy the values from the old predicate
    set {
      uid(v) <other> val(a) .
    }

    # and we delete the old predicate
    delete {
      uid(v) <age> * .
    }
  }
}' | jq

Result:

{
  "data": {
    "code": "Success",
    "message": "Done",
    "uids": {}
  },
  "extensions": {...}
}

Here, variable a will store a mapping from all the UIDs to their age. The mutation block then stores the corresponding value of age for each UID in the other predicate and deletes the age predicate.

We can achieve the same result using json dataset as follows:

curl -H "Content-Type: application/json" -X POST localhost:8080/mutate?commitNow=true -d $'{
  "query": "{ v as var(func: regexp(email, /.*@company1.io$/)) }",
  "delete": {
    "uid": "uid(v)",
    "age": null
  },
  "set": {
    "uid": "uid(v)",
    "other": "val(a)"
  }
}' | jq

Bulk Delete Example

Let’s say we want to delete all the users of company1 from the database. This can be achieved in just one query using the upsert block as follows:

curl -H "Content-Type: application/rdf" -X POST localhost:8080/mutate?commitNow=true -d $'
upsert {
  query {
    v as var(func: regexp(email, /.*@company1.io$/))
  }

  mutation {
    delete {
      uid(v) <name> * .
      uid(v) <email> * .
      uid(v) <age> * .
    }
  }
}' | jq

We can achieve the same result using json dataset as follows:

curl -H "Content-Type: application/json" -X POST localhost:8080/mutate?commitNow=true -d '{
  "query": "{ v as var(func: regexp(email, /.*@company1.io$/)) }",
  "delete": {
    "uid": "uid(v)",
    "name": null,
    "email": null,
    "age": null
  }
}' | jq