Index

A  B  C  D  E  F  G  I  J  L  M  O  P  Q  R  S  T  V  

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A

• access Python client in OCI Data Science notebook 13
• administrator dashboard for the graph server 21.1
• aggregations in GRAPH_TABLE 6.6
• APEX Graph Visualization plug-in 10
  • advanced options 10.3.8
  • appearance 10.3.2
  • base styles 10.3.8.3
  • callbacks options 10.3.9
  • captions 10.3.4
  • evolution 10.3.5
  • evolution settings 10.3.8.5
  • expand 10.3.7
  • general settings 10.3.8.1
  • layout 10.3.3
  • rule-based styles 10.3.8.2
  • schema 10.3.6
  • schema settings 10.3.8.6
  • settings 10.3.1
  • Smart Groups 10.3.8.4
• architecture models 1.3
• Autonomous AI Database graph client 17.2

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B

• binding_count in GRAPH_TABLE 6.6

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C

• create a SQL property graph
  • using views 5.1.8

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D

• DBMS_METADATA package 5.1.7

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E

• edge graph element tables 5.1.1
• edge table keys for SQL property graphs 5.1.2
• ELEMENT_NUMBER in GRAPH_TABLE 6.5.3
• enforced mode 5.1.4

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F

• functions
  • EDGE_ID 6.4
  • VERTEX_ID 6.4

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G

• GRAPH_TABLE operator 6
• graph pattern 6.1
  • path variables 6.1.2
• graphs
  • administrator dashboard for the graph server 21.1.3
• graph server (PGX) and client
  • installation 19
  • workflow 19.1
• graph visualization application VI
  • embedding graph visualization library 27
  • importing and exporting settings 26.8.4
  • legend panel 26.6
  • managing graph display size 26.7
  • running the web application 19.3.2
  • using cluster layout 26.8.1
  • using geographical layout 26.8.2
  • using network evolution 26.8.3
  • using the graph visualization application 26
    • visualizing graph queries on SQL property graphs 26.1
    • visualizing PGQL queries
      • graphs in the graph server(PGX) 26.2
      • PGQL property graphs 26.3
  • visualization modes 26.5
  • visualization settings 26.8
• graph visualization extension for VS Code 11
  • visualization settings 11.1

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I

• import graph data from Neo4j 4.2
  • gather metadata 4.2.4
  • into Autonomous AI Database 4.2.3
• installing graph visualization extension for Jupyter 12.1

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J

• Jupyter Notebook 17.4

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L

• labels and properties for SQL property graphs 5.1.3
• loading graph into graph server (PGX)
  • PGQL property graphs 15
  • SQL property graphs 8
  • with composite keys 8.8
• log management in the graph server (PGX) 34

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M

• MATCHNUM in GRAPH_TABLE 6.5.1
• memory consumption by the graph server 29
• memory usage dashboard 21.1.1
• migrate_pgql_to_sql() 9.3
• migrating PGQL to SQL property graph 9.3
• mixed property types 5.1.4

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O

• OPG4J shell 17.1.1
• OPG4Py shell 17.1.2
• OPTIONAL MATCH 23.3.7
• oraclegraph API reference
  • GraphVisualization 12.6.1
  • PgqlGraphVisualization 12.6.3
  • PgxGraphVisualization 12.6.4
  • SqlGraphVisualization 12.6.2
• Oracle Graph clients
  • Java client 19.3.1.1
    • from Oracle Graph Server and Client downloads 19.3.1.1.1
    • on Maven Central 19.3.1.1.2
  • Python client 19.3.1.2
    • from Oracle Graph server and Client downloads 19.3.1.2.3
    • from PyPI 19.3.1.2.1
    • in embedded mode 19.3.1.2.4
    • upgrade 19.3.1.2.2
• Oracle Graph Server (PGX)
  • configuration
    • graph server configuration parameters in server.conf file 20.1.2
    • runtime configuration parameters in pgx.conf file 28.1
  • connecting to the graph server 20.2
  • installation 19.2
    • deploying behind a load balancer 30
    • deploy to Apache Tomcat 19.2.3.1
    • deploy to Oracle WebLogic server 19.2.3.2
    • rpm 19.2.2
  • learn about the graph server 1.4
  • log management 34
  • starting the graph server 20.1
  • using the graph server V
  • working with files 33

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P

• PATH_NAME in GRAPH_TABLE 6.5.2
• path variables 6.1.2
• PGQL (Property Graph Query Language) 18
• PGQL property graphs III
  • creating graphs 14.1
  • GraphSON file import 14.2
  • metadata tables 14.1.1
  • privileges 14.1.2
  • quick start 16
• PgxML for Graphs 22
  • DeepWalk Algorithm 22.1
  • Pg2vec Algorithm 22.7
  • Supervised GraphWise Algorithm 22.2
  • Unsupervised GraphWise Algorithm 22.4, 22.6
• property graph
  • architecture 1.3
  • introduction 1
• Property Graph Query Language (PGQL) 18

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Q

• quickstart container image
  • Podman 2

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R

• REST API for Graph Server (PGX) 24
• REST endpoints for the graph server
  • v2
    • cancel an asynchronous query execution 24.7.4
    • check asynchronous query completion 24.7.2
    • get an authentication token 24.1
    • get graphs for a driver 24.3
    • get the database version 24.5
    • get user 24.6
    • refresh an authentication token 24.2
    • retrieve ansynchronous query result 24.7.3
    • run a PGQL query 24.4
    • run a PGQL query asynchronously 24.7.1

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S

• schema visualization of PGQL property graphs 26.4.2
• schema visualization of SQL property graphs 26.4.1
• sessions 32.4
  • administrator dashboard for the graph server 21.1.2
  • create 32.4.1
  • destroy 32.4.3
  • update 32.4.2
• setting up TLS (Transport layer Security) 19.4
  • using self-signed server keystore 19.4.1
• SQLcl 17.5.1
• SQL Developer
  • querying PGQL property graphs 17.5.2
  • querying SQL property graphs 6.15
• SQL graph queries 6
  • aggregate functions 6.6
  • at specific SCN 6.9
  • complex path patterns 6.3
  • ELEMENT_NUMBER 6.5.3
  • graph pattern 6.1
  • MATCHNUM 6.5.1
  • ONE ROW PER clause 6.5
  • PATH_NAME 6.5.2
  • variable length path pattern 6.2
• SQL property graphs II
  • add a comment to a SQL property graph 5.2
  • create a SQL property graph 5.1
  • drop a SQL property graph 5.5
  • granting privileges 5.1.5
  • metadata tables 5.1.6
  • quick start 4.1
  • rename a SQL property graph 5.4
  • revalidate a SQL property graph 5.3
  • SQL graph queries 6
    • examples 6.11
  • using JSON columns 5.6
  • visualization using APEX Graph Visualization plug-in 10
• sql property graph visualization in a Jupyter notebook 12.5
• subgraph loading for PGQL property graphs 15.2
• subgraph loading for SQL property graphs 8.2

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T

• trusted mode 5.1.4
• tuning SQL property graphs 6.13

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V

• vertex graph element tables 5.1.1
• vertex table keys for SQL property graphs 5.1.2