Examples of Neptune transaction semantics

The following examples illustrate different use cases for transaction semantics in Amazon Neptune.

Example 1 – Inserting a Property Only If It Does Not Exist

Suppose that you want to ensure that a property is set only once. For example, suppose that multiple queries are trying to assign a person a credit score concurrently. You only want one instance of the property to be inserted, and the other queries to fail because the property has already been set.

# GREMLIN:
g.V('person1').hasLabel('Person').coalesce(has('creditScore'), property('creditScore', 'AAA+'))

# SPARQL:
INSERT { :person1 :creditScore "AAA+" .}
WHERE  { :person1 rdf:type :Person .
         FILTER NOT EXISTS { :person1 :creditScore ?o .} }

The Gremlin property() step inserts a property with the given key and value. The coalesce() step executes the first argument in the first step, and if it fails, then it executes the second step:

Before inserting the value for the creditScore property for a given person1 vertex, a transaction must try to read the possibly non-existent creditScore value for person1. This attempted read locks the SP range for S=person1 and P=creditScore in the SPOG index where the creditScore value either exists or will be written.

Taking this range lock prevents any concurrent transaction from inserting a creditScore value concurrently. When there are multiple parallel transactions, at most one of them can update the value at a time. This rules out the anomaly of more than one creditScore property being created.

Example 2 – Asserting That a Property Value Is Globally Unique

Suppose that you want to insert a person with a Social Security number as a primary key. You would want your mutation query to guarantee that, at a global level, no one else in the database has that same Social Security number:

# GREMLIN:
g.V().has('ssn', 123456789).fold()
  .coalesce(__.unfold(),
            __.addV('Person').property('name', 'John Doe').property('ssn', 123456789'))

# SPARQL:
INSERT { :person1 rdf:type :Person .
         :person1 :name "John Doe" .
         :person1 :ssn 123456789 .}
WHERE  { FILTER NOT EXISTS { ?person :ssn 123456789 } }

This example is similar to the previous one. The main difference is that the range lock is taken on the POGS index rather than the SPOG index.

The transaction executing the query must read the pattern, ?person :ssn 123456789, in which the P and O positions are bound. The range lock is taken on the POGS index for P=ssn and O=123456789.

Example 3 – Changing a Property If Another Property Has a Specified Value

Suppose that various events in a game move a person from level one to level two, and assign them a new level2Score property set to zero. You need to be sure that multiple concurrent instances of such a transaction could not create multiple instances of the level-two score property. The queries in Gremlin and SPARQL might look like the following.

# GREMLIN:
g.V('person1').hasLabel('Person').has('level', 1)
 .property('level2Score', 0)
 .property(Cardinality.single, 'level', 2)

# SPARQL:
DELETE { :person1 :level 1 .}
INSERT { :person1 :level2Score 0 .
         :person1 :level 2 .}
WHERE  { :person1 rdf:type :Person .
         :person1 :level 1 .}

In Gremlin, when Cardinality.single is specified, the property() step either adds a new property or replaces an existing property value with the new value that is specified.

Any update to a property value, such as increasing the level from 1 to 2, is implemented as a deletion of the current record and insertion of a new record with the new property value. In this case, the record with level number 1 is deleted and a record with level number 2 is reinserted.

For the transaction to be able to add level2Score and update the level from 1 to 2, it must first validate that the level value is currently equal to 1. In doing so, it takes a range lock on the SPO prefix for S=person1, P=level, and O=1 in the SPOG index. This lock prevents concurrent transactions from deleting the version 1 triple, and as a result, no conflicting concurrent updates can happen.

Example 4 – Replacing an Existing Property

Certain events might update a person's credit score to a new value (here BBB). But you want to be sure that concurrent events of that type can't create multiple credit score properties for a person.

# GREMLIN:
g.V('person1').hasLabel('Person')
 .sideEffect(properties('creditScore').drop())
 .property('creditScore', 'BBB')

# SPARQL:
DELETE { :person1 :creditScore ?o .}
INSERT { :person1 :creditScore "BBB" .}
WHERE  { :person1 rdf:type :Person .
         :person1 :creditScore ?o .}

This case is similar to example 3, except that instead of locking the SPO prefix, Neptune locks the SP prefix with S=person1 and P=creditScore only. This prevents concurrent transactions from inserting or deleting any triples with the creditScore property for the person1 subject.

Example 5 – Avoiding Dangling Properties or Edges

The update on an entity should not leave a dangling element, that is, a property or edge associated to an entity that is not typed. This is only an issue in SPARQL, because Gremlin has built-in constraints to prevent dangling elements.

# SPARQL:
tx1: INSERT { :person1 :age 23 } WHERE { :person1 rdf:type :Person }
tx2: DELETE { :person1 ?p ?o }

The INSERT query must read and lock the SPO prefix with S=person1, P=rdf:type, and O=Person in the SPOG index. The lock prevents the DELETE query from succeeding in parallel.

In the race between the DELETE query trying to delete the :person1 rdf:type :Person record and the INSERT query reading the record and creating a range lock on its SPO in the SPOG index, the following outcomes are possible:

In all these different possible sequences of events, no dangling edge is created.