Transaction
Creating a transaction involves managing a sequence of operations that either all succeed or all fail. To explicitly roll back a transaction, such as from a conditional code block, you can call the failure method, which ensures the transaction is unconditionally rolled back at the end of the block. Calling the success method or the failure method does not inherently trigger a rollback by default.
In Neo4j, it's possible to define the name of the USER tag as a schema-indexable property within a transaction. This allows for the actual setting of a real user value through a separate transaction, enabling more structured and queryable data management.
Many database systems use locking mechanisms to manage concurrent access. Neo4j transactions control access to graph resources (nodes and relationships) using read and write locks. Multiple read locks on the same resource can coexist across threads, but only one write lock can be held at any given time, and no other active locks—read or write—can exist simultaneously.
By default, Neo4j does not automatically acquire read locks. Therefore, data reads reflect the last committed state of nodes, relationships, and indexes unless local modifications (even if not yet committed) are visible within the same transaction. Write locks, however, are automatically acquired when changes are made to any graph resource and remain in effect until the transaction completes.
If higher isolation is needed to prevent others from modifying a graph resource during reading, Neo4j allows for an explicit read lock. This requires an additional step to request the lock before accessing properties, as shown in Listing 7-5.
Avoiding system-level locks when reading data is advisable. It can lead to increased memory usage and potential blocking of write operations, as threads holding read locks must wait for the lock to be released before making updates.
Deadlocks can occur when two transactions attempt to acquire locks in different orders on the same set of nodes. Neo4j has a built-in mechanism to detect deadlocks and throws a `DeadlockDetectedException`, rolling back the transaction. This detection only works when Neo4j manages the locks, either through its default mechanisms or via its API methods like `acquireReadLock` and `acquireWriteLock`. External mechanisms like Java’s `synchronized` keywords may not be detected, potentially leading to application freezes.
To handle deadlocks effectively, always use Neo4j’s core API and avoid external locking mechanisms. This ensures proper deadlock detection and maintains data consistency. Additionally, ensure that graph resources are accessed in a consistent order to prevent deadlocks.
Deep Traversal
Traversal Order
Each time a visitor accesses a node, they must decide which next node to visit. This process continues until the traversal ends. Choosing the right path can result in quick completion with minimal memory usage. The two main sequential algorithms used in graph theory are depth-first and breadth-first traversals, which are commonly implemented in Neo4j.
Depth-First Traversal
In a depth-first approach, the algorithm first explores the first unvisited child of the current node. If all children have been visited, it backtracks to the most recent node that still has unvisited children.
Using Neo4j's API for a depth-first traversal of the entire graph is straightforward. Depth-first traversal is the default strategy in Neo4j. When creating a traversal description, if no specific order is provided, the system defaults to a depth-first approach.
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