UPSERT

The UPSERT keyword can be used for checking whether certain documents exist, and to update/replace them in case they exist, or create them in case they do not exist.

Each UPSERT operation is restricted to a single collection, and the collection name must not be dynamic. Only a single UPSERT statement per collection is allowed per AQL query, and it cannot be followed by read or write operations that access the same collection, by traversal operations, or AQL functions that can read documents.

Syntax

The syntax for upsert and repsert operations is:

UPSERT searchExpression INSERT insertExpression UPDATE updateExpression IN collection
UPSERT searchExpression INSERT insertExpression REPLACE updateExpression IN collection

Both variants can optionally end with an OPTIONS { … } clause.

When using the UPDATE variant of the upsert operation, the found document will be partially updated, meaning only the attributes specified in updateExpression will be updated or added. When using the REPLACE variant of upsert (repsert), existing documents will be replaced with the contexts of updateExpression.

Updating a document will modify the document’s revision number with a server-generated value. The system attributes _id, _key and _rev cannot be updated, _from and _to can.

The searchExpression contains the document to be looked for. It must be an object literal without dynamic attribute names. In case no such document can be found in collection, a new document will be inserted into the collection as specified in the insertExpression.

In case at least one document in collection matches the searchExpression, it will be updated using the updateExpression. When more than one document in the collection matches the searchExpression, it is undefined which of the matching documents will be updated. It is therefore often sensible to make sure by other means (such as unique indexes, application logic etc.) that at most one document matches searchExpression.

The following query will look in the users collection for a document with a specific name attribute value. If the document exists, its logins attribute will be increased by one. If it does not exist, a new document will be inserted, consisting of the attributes name, logins, and dateCreated:

UPSERT { name: 'superuser' } 
INSERT { name: 'superuser', logins: 1, dateCreated: DATE_NOW() } 
UPDATE { logins: OLD.logins + 1 } IN users

Note that in the UPDATE case it is possible to refer to the previous version of the document using the OLD pseudo-value.

Query options

ignoreErrors

The ignoreErrors option can be used to suppress query errors that may occur when trying to violate unique key constraints.

keepNull

When updating or replacing an attribute with a null value, ArangoDB will not remove the attribute from the document but store a null value for it. To get rid of attributes in an upsert operation, set them to null and provide the keepNull option.

mergeObjects

The option mergeObjects controls whether object contents will be merged if an object attribute is present in both the UPDATE query and in the to-be-updated document.

waitForSync

To make sure data are durable when an update query returns, there is the waitForSync query option.

ignoreRevs

In order to not accidentally update documents that have been written and updated since you last fetched them you can use the option ignoreRevs to either let ArangoDB compare the _rev value and only succeed if they still match, or let ArangoDB ignore them (default):

FOR i IN 1..1000
  UPSERT { _key: CONCAT('test', i)}
    INSERT {foobar: false}
    UPDATE {_rev: "1287623", foobar: true }
  IN users OPTIONS { ignoreRevs: false }

exclusive

The RocksDB engine does not require collection-level locks. Different write operations on the same collection do not block each other, as long as there are no write-write conflicts on the same documents. From an application development perspective it can be desired to have exclusive write access on collections, to simplify the development. Note that writes do not block reads in RocksDB. Exclusive access can also speed up modification queries, because we avoid conflict checks.

Use the exclusive option to achieve this effect on a per query basis:

FOR i IN 1..1000
  UPSERT { _key: CONCAT('test', i) }
  INSERT { foobar: false }
  UPDATE { foobar: true }
  IN users OPTIONS { exclusive: true }

Returning documents

UPSERT statements can optionally return data. To do so, they need to be followed by a RETURN statement (intermediate LET statements are allowed, too). These statements can optionally perform calculations and refer to the pseudo-values OLD and NEW. In case the upsert performed an insert operation, OLD will have a value of null. In case the upsert performed an update or replace operation, OLD will contain the previous version of the document, before update/replace.

NEW will always be populated. It will contain the inserted document in case the upsert performed an insert, or the updated/replaced document in case it performed an update/replace.

This can also be used to check whether the upsert has performed an insert or an update internally:

UPSERT { name: 'superuser' } 
INSERT { name: 'superuser', logins: 1, dateCreated: DATE_NOW() } 
UPDATE { logins: OLD.logins + 1 } IN users
RETURN { doc: NEW, type: OLD ? 'update' : 'insert' }

Transactionality

On a single server, upserts are executed transactionally in an all-or-nothing fashion.

If the RocksDB engine is used and intermediate commits are enabled, a query may execute intermediate transaction commits in case the running transaction (AQL query) hits the specified size thresholds. In this case, the query’s operations carried out so far will be committed and not rolled back in case of a later abort/rollback. That behavior can be controlled by adjusting the intermediate commit settings for the RocksDB engine.

For sharded collections, the entire query and/or upsert operation may not be transactional, especially if it involves different shards and/or DB-Servers.

Limitations

• The lookup and the insert/update/replace parts are executed one after another, so that other operations in other threads can happen in between. This means if multiple UPSERT queries run concurrently, they may all determine that the target document does not exist and then create it multiple times!

  Note that due to this gap between the lookup and insert/update/replace, even with a unique index there may be duplicate key errors or conflicts. But if they occur, the application/client code can execute the same query again.

  To prevent this from happening, one should add a unique index to the lookup attribute(s). Note that in the cluster a unique index can only be created if it is equal to the shard key attribute of the collection or at least contains it as a part.

  An alternative to making an UPSERT statement work atomically is to use the exclusive option to limit write concurrency for this collection to 1, which helps avoiding conflicts but is bad for throughput!

• Using very large transactions in an UPSERT (e.g. UPSERT over all documents in a collection) an intermediate commit can be triggered. This intermediate commit will write the data that has been modified so far. However this will have the side-effect that atomicity of this operation cannot be guaranteed anymore and that ArangoDB cannot guarantee to that read your own writes in upsert will work.

  This will only be an issue if you write a query where your search condition would hit the same document multiple times, and only if you have large transactions. In order to avoid this issues you can increase the intermediateCommit thresholds for data and operation counts.

• The lookup attribute(s) from the search expression should be indexed in order to improve UPSERT performance. Ideally, the search expression contains the shard key, as this allows the lookup to be restricted to a single shard.