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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.
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 database servers.
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.
The syntax for an upsert operation is:
UPSERT searchExpression INSERT insertExpression UPDATE updateExpression IN collection options
UPSERT searchExpression INSERT insertExpression REPLACE updateExpression IN collection options
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, 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.
Setting query options
As in several above examples, the ignoreErrors option can be used to suppress query errors that may occur when trying to violate unique key constraints.
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.
There is also the option mergeObjects that 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.
Note: the default value for mergeObjects is true, so there is no need to specify it explicitly.
To make sure data are durable when an update query returns, there is the waitForSync query option.
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 }
NOTE: You need to add the _rev
value in the updateExpression, it will not be used within
the searchExpression. Even worse, if you use an outdated _rev
in the searchExpression
UPSERT will trigger the INSERT path instead of the UPDATE path, because it has not found a document
exactly matching the searchExpression.
In contrast to the MMFiles engine, 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' }
Limitations
-
The lookup and the insert/update/replace parts are executed non-atomically. That 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 the non-atomicity of 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.