Restore contsel/contjoinsel for containment & key-existence operators (#2356) (#2417) The containment (`@>`, `<@`, `@>>`, `<<@`) and key-existence (`?`, `?|`, `?&`) operators on `agtype` were bound to `matchingsel`/`matchingjoinsel` on the PG14+ source tree. `matchingsel` is built for pattern operators (LIKE/regex) and during planning invokes the operator's underlying function (`agtype_contains`) once per `pg_statistic` MCV. With realistic statistics targets that produces a planner-time regression that dominates simple OLTP-style point queries. Rebind those operators to the lighter `contsel`/`contjoinsel` estimators, which return fixed selectivity constants without invoking the operator function during planning. This is a deliberate planning-speed vs. estimate-accuracy trade-off. Note it DIVERGES from PostgreSQL core, which keeps jsonb's `@>`, `<@`, `?`, `?|`, `?&` on `matchingsel`/`matchingjoinsel` (verified on REL_16/17/18_STABLE in `pg_operator.dat`); it is an AGE-specific choice favoring workloads where these operators appear in selective point lookups. A future improvement could add a custom `agtype` selectivity function that is both cheap and statistics-aware. Changes: * `sql/agtype_operators.sql`, `sql/agtype_exists.sql`: 10 operators flipped from `matchingsel`/`matchingjoinsel` to `contsel`/`contjoinsel`. * `age--1.7.0--y.y.y.sql`: appended `ALTER OPERATOR ... SET (RESTRICT, JOIN)` for all 10 operators so existing installs flip on `ALTER EXTENSION age UPDATE`. * `regress/sql/containment_selectivity.sql` (+ `expected/.out`): pin the bindings via `pg_operator`, plus a scoped "no leaked matchingsel" guard and functional smoke for all 10 operators. Adds an upgrade-path assertion that simulates a stale (pre-fix) install, replays the shipped `ALTER OPERATOR` block, and confirms every overload flips to `contsel`/`contjoinsel` (run in a rolled-back transaction). * `regress/expected/cypher_match.out`, `regress/expected/cypher_vle.out`: refresh expected to reflect new (and better) plan shapes that the lower-selectivity helper produces — `test_enable_containment` now picks Nested Loop + Index Only Scans over a Seq Scan/Hash Join, and two `MATCH p=...` and `show_list_use_vle` queries flip row order (queries had no `ORDER BY`; result set is unchanged, only ordering). * `Makefile`: register `containment_selectivity` in `REGRESS`. Validation: * Build: clean, `-Werror`. * Regression: 36/37 tests pass under `EXTRA_TESTS="pgvector fuzzystrmatch pg_trgm"`. Only `age_upgrade` fails — pre-existing on master at 774e781b (verified by `git stash && installcheck`). * Reporter's exact methodology (LDBC-SNB-style snb_graph + pgbench on `bench_message_content`) reproduces the regression and the fix: | Metric | matchingsel | contsel | Delta | |----------------------------|-------------|---------|-------| | EXPLAIN planning time (ms) | 1.42 | 0.97 | -32% | | EXPLAIN execution time (ms)| 0.34 | 0.31 | ~equal| | pgbench TPS (8c x 30s) | 5247 | 7378 | +40.6%| Run with `default_statistics_target = 1000` to populate MCV lists, matching the reporter's analyzed-graph conditions. * Upgrade path: validated end-to-end during the benchmark — operator bindings were flipped from `matchingsel` -> `contsel` via the same `ALTER OPERATOR` statements the upgrade SQL ships, while operators remained functional throughout. Driver workflows (python/go/node/jdbc) intentionally not run: this PR only adjusts pg_operator selectivity metadata. There is no C, type, or protocol change that drivers could observe. Closes #2356.
Apache AGE is an extension for PostgreSQL that enables users to leverage a graph database on top of the existing relational databases. AGE is an acronym for A Graph Extension and is inspired by Bitnine's AgensGraph, a multi-model database fork of PostgreSQL. The basic principle of the project is to create a single storage that handles both the relational and graph data model so that the users can use the standard ANSI SQL along with openCypher, one of the most popular graph query languages today. There is a strong need for cohesive, easy-to-implement multi-model databases. As an extension of PostgreSQL, AGE supports all the functionalities and features of PostgreSQL while also offering a graph model to boot.
Apache AGE is :
Refer to our latest Apache AGE documentation to learn about installation, features, built-in functions, and Cypher queries.
Install the following essential libraries according to each OS. Building AGE from the source depends on the following Linux libraries (Ubuntu package names shown below):
yum install gcc glibc glib-common readline readline-devel zlib zlib-devel flex bison
dnf install gcc glibc bison flex readline readline-devel zlib zlib-devel
sudo apt-get install build-essential libreadline-dev zlib1g-dev flex bison
Apache AGE is intended to be simple to install and run. It can be installed with Docker and other traditional ways.
You will need to install an AGE compatible version of Postgres, for now AGE supports Postgres 11, 12, 13, 14, 15, 16, 17 & 18. Supporting the latest versions is on AGE roadmap.
You can use a package management that your OS provides to download PostgreSQL.
sudo apt install postgresql
You can download the Postgres source code and install your own instance of Postgres. You can read instructions on how to install from source code for different versions on the official Postgres Website.
Clone the github repository or download the download an official release. Run the pg_config utility and check the version of PostgreSQL. Currently, only PostgreSQL versions 11, 12, 13, 14, 15, 16, 17 & 18 are supported. If you have any other version of Postgres, you will need to install PostgreSQL version 11, 12, 13, 14, 15, 16, 17 & 18.
pg_config
Run the following command in the source code directory of Apache AGE to build and install the extension.
make install
If the path to your Postgres installation is not in the PATH variable, add the path in the arguments:
make PG_CONFIG=/path/to/postgres/bin/pg_config install
docker pull apache/age
docker run \ --name age \ -p 5455:5432 \ -e POSTGRES_USER=postgresUser \ -e POSTGRES_PASSWORD=postgresPW \ -e POSTGRES_DB=postgresDB \ -d \ apache/age
docker exec -it age psql -d postgresDB -U postgresUser
For every connection of AGE you start, you will need to load the AGE extension.
CREATE EXTENSION age;
LOAD 'age';
SET search_path = ag_catalog, "$user", public;
If you are using AGE from a database client that does not default to autocommit — most commonly psycopg v3 or JDBC — you must understand how PostgreSQL‘s transaction semantics apply to AGE’s setup and DDL-like functions. Otherwise, you may see graphs or labels that appear to be created successfully, but are not visible from new connections.
This is not a bug in AGE — it is standard PostgreSQL behavior. AGE's DDL-like functions write to the catalog, and catalog writes only become visible to other sessions after the enclosing transaction is committed.
| Statement | Scope | Needs commit to be visible elsewhere? |
|---|---|---|
LOAD 'age' | Session-local (loads the .so into the current backend) | No |
SET search_path = ag_catalog, "$user", public | Session-local | No |
SELECT create_graph('g') | Writes to ag_graph and creates a schema | Yes |
SELECT create_vlabel('g', 'L') / create_elabel(...) | Writes to ag_label and creates a table | Yes |
SELECT drop_graph('g', true) / drop_label(...) | Writes to catalog | Yes |
SELECT load_labels_from_file(...) / load_edges_from_file(...) | Writes to catalog + data | Yes |
cypher('g', $$ CREATE (:L {...}) $$) | Writes data | Yes |
In a client that defaults to autocommit (e.g. psql), every statement commits automatically, so this is never noticed. In a non-autocommit client, the first statement you run implicitly opens a transaction that stays open until you call commit(), rollback(), or close the connection.
The common pitfall is that with connection.transaction(): in psycopg does not start a new top-level transaction when one is already open — it creates a savepoint inside the existing outer transaction. Releasing a savepoint is not a commit, so your create_graph write stays invisible to other sessions until the outer transaction is explicitly committed.
import psycopg params = {"host": "localhost", "port": 5432, "user": "postgres", "password": "pw", "dbname": "mydb"} # --- First connection --- conn = psycopg.connect(**params) conn.execute("LOAD 'age'") # implicitly opens a txn conn.execute("SET search_path = ag_catalog, '$user', public") with conn.transaction(), conn.cursor() as cur: # <-- SAVEPOINT, not a real txn cur.execute("SELECT * FROM create_graph('my_graph')") # outer transaction is STILL OPEN here conn.close() # outer transaction is rolled back on close → my_graph is gone # --- New connection --- conn = psycopg.connect(**params) conn.execute("LOAD 'age'") conn.execute("SET search_path = ag_catalog, '$user', public") with conn.cursor() as cur: cur.execute("SELECT name FROM ag_graph;") # 'my_graph' is NOT in the results
commit() after setupconn = psycopg.connect(**params) conn.execute("LOAD 'age'") conn.execute("SET search_path = ag_catalog, '$user', public") conn.commit() # <-- closes the implicit outer txn with conn.transaction(), conn.cursor() as cur: cur.execute("SELECT * FROM create_graph('my_graph')") # this transaction block is now top-level and commits on exit conn.close()
conn = psycopg.connect(**params, autocommit=True) conn.execute("LOAD 'age'") conn.execute("SET search_path = ag_catalog, '$user', public") conn.execute("SELECT * FROM create_graph('my_graph')") # commits immediately conn.close()
You can also toggle autocommit at runtime with conn.set_autocommit(True).
JDBC connections also default to autocommit true per the JDBC spec, but many frameworks (Spring, etc.) flip it off. If you are running AGE DDL-like calls from JDBC, either:
connection.setAutoCommit(true); // ... LOAD 'age'; SET search_path ...; SELECT create_graph(...);
or keep autocommit off and explicitly commit after DDL-like calls:
stmt.execute("LOAD 'age'"); stmt.execute("SET search_path = ag_catalog, \"$user\", public;"); stmt.execute("SELECT create_graph('my_graph');"); connection.commit(); // make the graph visible to other sessions
If an AGE call creates, drops, or modifies a graph, label, vertex, edge, or property, it is a transactional write. In a non-autocommit client, it will not be visible to other sessions until you explicitly
commit().
To create a graph, use the create_graph function located in the ag_catalog namespace.
SELECT create_graph('graph_name');
To create a single vertex with label and properties, use the CREATE clause.
SELECT * FROM cypher('graph_name', $$ CREATE (:label {property:"Node A"}) $$) as (v agtype);
SELECT * FROM cypher('graph_name', $$ CREATE (:label {property:"Node B"}) $$) as (v agtype);
To create an edge between two nodes and set its properties:
SELECT * FROM cypher('graph_name', $$ MATCH (a:label), (b:label) WHERE a.property = 'Node A' AND b.property = 'Node B' CREATE (a)-[e:RELTYPE {property:a.property + '<->' + b.property}]->(b) RETURN e $$) as (e agtype);
And to query the connected nodes:
SELECT * from cypher('graph_name', $$
MATCH (V)-[R]-(V2)
RETURN V,R,V2
$$) as (V agtype, R agtype, V2 agtype);
Starting with Apache AGE is very simple. You can easily select your platform and incorporate the relevant SDK into your code.
Apache AGE Viewer is a user interface for Apache AGE that provides visualization and exploration of data. This web visualization tool allows users to enter complex graph queries and explore the results in graph and table forms. Apache AGE Viewer is enhanced to proceed with extensive graph data and discover insights through various graph algorithms. Apache AGE Viewer will become a graph data administration and development platform for Apache AGE to support multiple relational databases: https://github.com/apache/age-viewer.
This is a visualization tool. After installing AGE Extension, you may use this tool to get access to the visualization features.
You can also get help from these videos.
You can improve ongoing efforts or initiate new ones by sending pull requests to this repository. Also, you can learn from the code review process, how to merge pull requests, and from code style compliance to documentation by visiting the Apache AGE official site - Developer Guidelines. Send all your comments and inquiries to the user mailing list, users@age.apache.org.