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Update links with their redirects URLs. (#1334)
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modules/ROOT/pages/appendix/gql-conformance/supported-optional.adoc

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| * Feature GD01 implies compliance with GQL feature GT01, "Explicit transaction commands", which states that conforming languages shall contain the following transaction control commands: `START TRANSACTION`, `ROLLBACK`, and `COMMIT`.
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These are not present in Cypher.
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However, Neo4j offers transaction management through the link:{neo4j-docs-base-uri}/create-applications[driver] transaction API.
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Cypher Shell also offers specific link:{neo4j-docs-base-uri}/operations-manual/current/tools/cypher-shell/#cypher-shell-commands[commands] to manage transactions.
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Cypher Shell also offers specific link:{neo4j-docs-base-uri}/operations-manual/current/cypher-shell/#cypher-shell-commands[commands] to manage transactions.
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* Feature GD01 implies conformance to GQL's `<set-statement>` (subclause 13.3).
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GQL’s `SET` has no order dependencies because all right-hand side operations are completed before any assignments occur.
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However, In Cypher’s `SET`, the order of rows can affect the outcome because changes made during execution may depend on the sequence of assignments.

modules/ROOT/pages/appendix/gql-conformance/unsupported-mandatory.adoc

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| GQL defines the following transaction commands: `START TRANSACTION`, `COMMIT`, and `ROLLBACK`.
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Neo4j offers transaction management through the link:{neo4j-docs-base-uri}/create-applications[driver] transaction API.
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Cypher Shell also offers specific link:{neo4j-docs-base-uri}/operations-manual/current/tools/cypher-shell/#cypher-shell-commands[commands] to manage transactions.
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Cypher Shell also offers specific link:{neo4j-docs-base-uri}/operations-manual/current/cypher-shell/#cypher-shell-commands[commands] to manage transactions.
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| 11.1
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| Graph expressions

modules/ROOT/pages/clauses/delete.adoc

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[NOTE]
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====
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The `DETACH DELETE` clause may not be permitted to users with restricted security privileges.
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For more information, see link:{neo4j-docs-base-uri}/operations-manual/current/authentication-authorization/access-control#detach-delete-restricted-user[Operations Manual -> Fine-grained access control].
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For more information, see link:{neo4j-docs-base-uri}/operations-manual/current/tutorial/access-control/#detach-delete-restricted-user[Operations Manual -> Fine-grained access control].
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====
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modules/ROOT/pages/clauses/load-csv.adoc

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====
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[NOTE]
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For ways of importing data into an Aura instance, see link:https://neo4j.com/docs/aura/auradb/importing/importing-data/[Aura -> Importing data].
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For ways of importing data into an Aura instance, see link:https://neo4j.com/docs/aura/classic/auradb/importing/importing-data/[Aura -> Importing data].
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[TIP]
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When using `+file:///+` URLs, spaces and other non-alphanumeric characters must be link:https://developer.mozilla.org/en-US/docs/Glossary/percent-encoding[URL-encoded].
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When using `+file:///+` URLs, spaces and other non-alphanumeric characters must be link:https://developer.mozilla.org/en-US/docs/Glossary/Percent-encoding[URL-encoded].
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==== Configuration settings for file URLs
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=== Import data from relational databases
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If the source data comes from a relational model, it's worth evaluating how to gain the most from moving to a graph data model.
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Before running the import, think about how the data can be modeled as a graph, and adapt its structure accordingly when running the import (see link:https://neo4j.com/docs/getting-started/data-modeling/guide-data-modeling/[Graph data modeling]).
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Before running the import, think about how the data can be modeled as a graph, and adapt its structure accordingly when running the import (see link:https://neo4j.com/docs/getting-started/data-modeling/tutorial-data-modeling/[Graph data modeling]).
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Data from relational databases may consist of one or multiple CSV files, depending on the source database structure.
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A performant approach is to run multiple passes of `LOAD CSV` to import nodes separately from relationships.
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There are a few other tools to get CSV data into Neo4j.
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1. *The link:{neo4j-docs-base-uri}/operations-manual/current/tools/neo4j-admin/neo4j-admin-import/[`neo4j-admin database import`] command* is the most efficient way of importing large CSV files.
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1. *The link:{neo4j-docs-base-uri}/operations-manual/current/import/[`neo4j-admin database import`] command* is the most efficient way of importing large CSV files.
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2. Use a link:https://neo4j.com/docs/create-applications/[*language library*] to parse CSV data and run creation Cypher queries against a Neo4j database.
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Created as an extension library to provide common procedures and functions to developers.
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This library is especially helpful for complex transformations and data manipulations.

modules/ROOT/pages/functions/aggregating.adoc

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[TIP]
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====
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To learn more about how Cypher handles aggregations performed on zero rows, refer to link:https://neo4j.com/developer/kb/understanding-aggregations-on-zero-rows//[Neo4j Knowledge Base -> Understanding aggregations on zero rows].
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To learn more about how Cypher handles aggregations performed on zero rows, refer to link:https://neo4j.com/developer/kb/understanding-aggregations-on-zero-rows/[Neo4j Knowledge Base -> Understanding aggregations on zero rows].
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====
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== Example graph

modules/ROOT/pages/functions/graph.adoc

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.Considerations
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|===
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| `graph.names()` is only supported on link:{neo4j-docs-base-uri}/operations-manual/current/composite-databases[composite databases].
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| `graph.names()` is only supported on link:{neo4j-docs-base-uri}/operations-manual/current/database-administration/composite-databases/concepts/[composite databases].
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|===
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.Considerations
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|===
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| `graph.propertiesByName()` is only supported on link:{neo4j-docs-base-uri}/operations-manual/current/composite-databases[composite databases].
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| `graph.propertiesByName()` is only supported on link:{neo4j-docs-base-uri}/operations-manual/current/database-administration/composite-databases/concepts/[composite databases].
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| The properties in the returned `MAP` are set on the link:{neo4j-docs-base-uri}/operations-manual/current/database-administration/aliases/manage-aliases-standard-databases/[alias]that adds the graph as a constituent of a composite database.
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|===
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modules/ROOT/pages/genai-integrations.adoc

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There are 9083 `Movie` nodes with a `plot` and `title` property.
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To recreate the graph, download and import this link:https://github.com/neo4j-graph-examples/recommendations/raw/main/data/recommendations-embeddings-50.dump[dump file] to an empty Neo4j database.
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Dump files can be imported for both link:{neo4j-docs-base-uri}/aura/auradb/importing/import-database/[Aura] and link:{neo4j-docs-base-uri}/operations-manual/current/backup-restore/restore-dump/[on-prem] instances.
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Dump files can be imported for both link:{neo4j-docs-base-uri}/aura/classic/auradb/importing/import-database/[Aura] and link:{neo4j-docs-base-uri}/operations-manual/current/backup-restore/restore-dump/[on-prem] instances.
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[NOTE]
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The embeddings on this are generated using link:https://platform.openai.com/docs/guides/embeddings[OpenAI] (model `text-embedding-ada-002`), producing 1536-dimensional vectors.
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=== Vertex AI
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* Identifier (`provider` argument): `"VertexAI"`
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* https://cloud.google.com/vertex-ai/docs/generative-ai/embeddings/get-text-embeddings[Official Vertex AI documentation]
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* https://cloud.google.com/vertex-ai/generative-ai/docs/embeddings/get-text-embeddings[Official Vertex AI documentation]
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.Vertex AI provider details
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=== Azure OpenAI
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* Identifier (`provider` argument): `"AzureOpenAI"`
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* https://learn.microsoft.com/en-us/azure/ai-services/openai/[Official Azure OpenAI documentation]
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* https://learn.microsoft.com/en-us/azure/ai-foundry/[Official Azure OpenAI documentation]
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Unlike the other providers, the model is configured when creating the deployment on Azure, and is thus not part of the configuration map.

modules/ROOT/pages/indexes/search-performance-indexes/using-indexes.adoc

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In total, the graph contains 69165 nodes (of which 188 have the label `PointOfInterest`) and 152077 `ROUTE` relationships.
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To recreate the graph, download and import the link:https://github.com/neo4j-graph-examples/openstreetmap/raw/main/data/openstreetmap-50.dump[5.0 dump file] to an empty Neo4j database.
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Dump files can be imported for both link:{neo4j-docs-base-uri}/aura/auradb/importing/import-database/[Aura] and link:{neo4j-docs-base-uri}/operations-manual/current/backup-restore/restore-dump/[on-prem] instances.
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Dump files can be imported for both link:{neo4j-docs-base-uri}/aura/classic/auradb/importing/import-database/[Aura] and link:{neo4j-docs-base-uri}/operations-manual/current/backup-restore/restore-dump/[on-prem] instances.
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[[token-lookup-indexes]]
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== Token lookup indexes

modules/ROOT/pages/indexes/semantic-indexes/full-text-indexes.adoc

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* Full-text indexes can be queried using the Lucene query language.
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* Full-text indexes are kept up to date automatically, as nodes and relationships are added, removed, and modified.
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* Full-text indexes will automatically populate newly created indexes with the existing data in a store.
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* Full-text indexes can be checked by the link:{neo4j-docs-base-uri}/operations-manual/current/tools/neo4j-admin/consistency-checker[consistency checker], and they can be rebuilt if there is a problem with them.
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* Full-text indexes can be checked by the link:{neo4j-docs-base-uri}/operations-manual/current/backup-restore/consistency-checker/[consistency checker], and they can be rebuilt if there is a problem with them.
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* Newly created full-text indexes get automatically populated with the existing data in the database.
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* Full-text indexes are created, dropped, and updated transactionally, and are automatically replicated throughout a cluster.

modules/ROOT/pages/indexes/semantic-indexes/vector-indexes.adoc

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* link:https://neo4j.com/docs/genai/tutorials/embeddings-vector-indexes/[GenAI documentation -> Embeddings & Vector Indexes Tutorial]
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Neo4j vector indexes are powered by the link:https://lucene.apache.org/[Apache Lucene] indexing and search library.footnote:[Lucene implements a Hierarchical Navigable Small World (HNSW) Graph to perform a k approximate nearest neighbors (k-ANN) query over the vector fields.
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For more information, see link:http://dx.doi.org/10.1109/TPAMI.2018.2889473[Efficient and Robust Approximate Nearest Neighbor Search Using Hierarchical Navigable Small World Graphs] -- Yury A. Malkov and Dmitry A. Yashunin]
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For more information, see link:https://ieeexplore.ieee.org/document/8594636/[Efficient and Robust Approximate Nearest Neighbor Search Using Hierarchical Navigable Small World Graphs] -- Yury A. Malkov and Dmitry A. Yashunin]
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[[example-graph]]
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Dump files can be imported for both link:{neo4j-docs-base-uri}/aura/auradb/importing/import-database/[Aura] and link:{neo4j-docs-base-uri}/operations-manual/current/backup-restore/restore-dump/[on-prem] instances.
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Dump files can be imported for both link:{neo4j-docs-base-uri}/aura/classic/auradb/importing/import-database/[Aura] and link:{neo4j-docs-base-uri}/operations-manual/current/backup-restore/restore-dump/[on-prem] instances.
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The dump file used to load the dataset contains embeddings generated by https://openai.com/[OpenAI], using the model `text-embedding-ada-002`.

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