Querying OQL — quick reference

An OQL canister exposes two read-only methods:

Method	Returns	Purpose
`schema()`	one JSON `Text`	Catalogue of the canister's entities: each entity's primary key, fields, and edges.
`execute(qJson : text)`	typed Candid `Result`	Runs a JSON-encoded query and returns matching rows.

Calling the canister

The

icp

CLI is already installed and configured in the sandbox; the canister name

backend

resolves to the project's canister (no identity, no canister ID). Both methods are

query

calls, so every invocation uses

--query

bash

icp canister call backend schema '()' --query
icp canister call backend execute '("<json-query>")' --query

execute

takes one

text

argument — the JSON query embedded as a Candid text literal. Wrap the JSON in

("...")

and escape every

\"

. The query

{"start":"customer","limit":3}

becomes:

bash

icp canister call backend execute '("{\"start\":\"customer\",\"limit\":3}")' --query

schema()

returns its JSON the same way — a Candid

text

literal

("...escaped json...")

; unescape

\"

→

(and

\\

→

) to read it. Add

--branch live

to read the deployed canister instead of the draft (live is query-only). If a string value contains a single quote, escape it for the shell with

'\''

Recipe

Get the schema once.
```
icp canister call backend schema '()' --query
```
— cache it for the session; it changes only between deployments (§1).
Map the request to entities. Pick the entity that holds the answer. Use each field's
```
typeName
```
and
```
values
```
to choose literal types, and
```
role: {"edge": ...}
```
to see how entities connect.
Translate into one or more queries. Start from the entity whose rows you want (§2). Add
```
where
```
(§2.1),
```
orderBy
```
/
```
limit
```
/
```
offset
```
,
```
select
```
, and
```
aggregate
```
/
```
groupBy
```
(§2.2). Cross a forward edge with a dotted path in a single query (§4.1); a reverse one-to-many needs the parent keys first, then
```
in
```
(§4.2).
Run and read.
```
icp canister call backend execute '("<json>")' --query
```
— parse the Candid rows by cell
```
name
```
(§3); if
```
hasMore
```
, page with
```
offset
```
(§5).
Retry on traps. There is no error envelope — re-read the schema, fix the query, rerun (§6).

1. Discover —

schema

Fetch once and cache for the session — it only changes between canister deployments.

bash

icp canister call backend schema '()' --query

Read it like this:

name
→ entity name; use it as
```
start
```
in queries.
primaryKey
→ field whose value identifies a row. An edge
```
{"to": "<entity>"}
```
value is a primary-key value in that target.
fields
→ each field's
```
name
```
, scalar
```
typeName
```
, and
```
role
```
:
```
"payload"
```
(plain field) or
```
{"edge": {"to": "<entity>"}}
```
(a foreign key — how you traverse the graph). Names may carry a
```
__1
```
,
```
__2
```
, … suffix when two columns would share a name — use the exact names
```
schema()
```
reports.
values
(optional) → the exact literals a field can hold (typically a variant's arms). Filter with those literals, not guesses:
```
["free","pro","enterprise"]
```
means query
```
"enterprise"
```
, not
```
"Enterprise"
```
. Absent ⇒ unbounded — sample it with a query if you need candidates.
typeName
→ JSON literal type for
```
value
```
:
- ```
"Nat"
```
  → unsigned integer (
```
0
```
  ,
```
1
```
  , …)
- ```
"Int"
```
  → signed integer (
```
-1
```
  ,
```
0
```
  ,
```
1
```
  , …)
- ```
"Float"
```
  → JSON number with a decimal point (
```
0.5
```
  ,
```
-3.14
```
  ,
```
1.0e2
```
  ). A bare integer (
```
10
```
  ) is also accepted — numeric variants bridge, so
```
gt(price, 10)
```
  matches a
```
price : Float = 12.5
```
  row. Float equality is bitwise IEEE-754; use a range (
```
ge
```
  +
```
le
```
  ) for decimals like
```
0.42
```
  with no exact binary form.
- ```
"Bool"
```
  →
```
true
```
  /
```
false
```
- ```
"Text"
```
  → JSON string.
```
Principal
```
  fields report as
```
"Text"
```
  (canonical textual form) — filter them with a string value.

2. Form a query —

execute

A query is a single JSON object. Only

start

is required.

json

{
  "start":     "<entityName>",
  "where":     <Predicate>,
  "groupBy":   ["<fieldName>", ...],
  "aggregate": [{ "fn": "count|sum|avg|min|max", "field": "<fieldName>", "as": "<outName>" }, ...],
  "orderBy":   [{ "field": "<fieldName>", "dir": "asc|desc" }, ...],
  "offset":    <Nat>,
  "limit":     <Nat>,
  "select":    ["<fieldName>", ...]
}

Field	Default	Notes
`start`	(required)	An entity `name` from `schema()` .
`where`	omit ⇒ no filter	A single predicate (§2.1) — not wrapped in `{"filter": ...}` .
`groupBy`	`[]`	Bucket rows by these fields; one output row per distinct combination (§2.2).
`aggregate`	`[]`	Aggregates per bucket, or over all rows when `groupBy` is empty (§2.2).
`orderBy`	`[]` (canister-defined order, typically insertion order)	Multi-key sort, first clause primary. `dir` defaults `"asc"` .
`offset`	`0`	Drop the first N matches.
`limit`	every match	Keep at most N. `hasMore` in the result tells you if more exist.
`select`	every non-hidden field (or, when aggregating, group-key + aggregate columns)	Subset projection.

bash

icp canister call backend execute '("{\"start\":\"customer\",\"limit\":3}")' --query

Filter + sort + project — the core shape (

where

orderBy

limit

select

bash

icp canister call backend execute '("{\"start\":\"customer\",\"where\":{\"eq\":{\"field\":\"plan\",\"value\":\"enterprise\"}},\"orderBy\":[{\"field\":\"monthlyRevenueUsd\",\"dir\":\"desc\"}],\"limit\":5,\"select\":[\"companyName\",\"monthlyRevenueUsd\",\"accountManagerName\"]}")' --query

2.1 Predicate operators

Predicate

is a JSON object with exactly one key that names the operator.

Operator	Shape	Meaning
`eq` / `ne` / `lt` / `le` / `gt` / `ge`	`{"<op>": { "field": "<name>", "value": <scalar> } }`	Scalar relation.
`in`	`{"in": { "field": "<name>", "value": [<scalar>, ...] } }`	Membership; empty array matches nothing.
`contains` / `startsWith` / `endsWith`	`{"<op>": { "field": "<name>", "value": "<text>" } }`	Case-sensitive substring / prefix / suffix on `Text` — server-side scan, no need to page rows into context.
`icontains`	`{"icontains": { "field": "<name>", "value": "<text>" } }`	Case-insensitive `contains` . Prefer this for user-typed search terms.
`and` / `or` / `not`	`{"and": [<P>, ...]}` / `{"or": [<P>, ...]}` / `{"not": <P>}`	Boolean composition.

Text search runs server-side — "the customer whose name mentions north" is one query, not a row scan into context:

bash

icp canister call backend execute '("{\"start\":\"customer\",\"where\":{\"icontains\":{\"field\":\"companyName\",\"value\":\"north\"}},\"select\":[\"companyName\",\"accountManagerName\"]}")' --query

<scalar>

must match the field's

typeName

JSON	Maps to	Use for fields with typeName
`null`	`null_`	any nullable field (rare in `where` )
`true` / `false`	`bool`	`"Bool"`
`0` , `1` , `42`	`nat`	`"Nat"` (also matches `"Float"` via numeric bridging)
`-1` , `-42`	`int`	`"Int"` (also matches `"Float"` via numeric bridging)
`0.5` , `-3.14` , `1.0e2`	`float`	`"Float"`
`"foo"`	`text`	`"Text"`

A row whose field is

null_

fails every relation except

ne

. Filter by relationship with

field

"<edge>"

and

value

= the target entity's primary-key value; or read through an edge with

"<edge>.<targetField>"

(§4.1).

2.2 Aggregate — count, groupBy, sum/avg/min/max

Compute on the canister instead of fetching every row and tallying client-side.

fn

count

sum

avg

min

max

;

field

is required for every fn except

count

;

min

max

also work on text.

as

renames the output column (default

count

sum_<field>

, …) and must not contain

(dots are the edge-traversal separator — parse error). For a dotted

field

the default joins segments with

(

sum

dept.budget

→

sum_dept_budget

aggregate

with no

groupBy

→ one row over the whole filtered set (

count

of an empty match is

groupBy

with no

aggregate

→ a server-side DISTINCT. Output rows contain only the group-key + aggregate columns.

"How many enterprise customers?" —

count

over a filtered set, one row out:

bash

icp canister call backend execute '("{\"start\":\"customer\",\"where\":{\"eq\":{\"field\":\"plan\",\"value\":\"enterprise\"}},\"aggregate\":[{\"fn\":\"count\"}]}")' --query

"Which account manager has the most customers, and total MRR?" —

groupBy

count

sum

bash

icp canister call backend execute '("{\"start\":\"customer\",\"groupBy\":[\"accountManager\"],\"aggregate\":[{\"fn\":\"count\"},{\"fn\":\"sum\",\"field\":\"monthlyRevenueUsd\",\"as\":\"mrr\"}],\"orderBy\":[{\"field\":\"count\",\"dir\":\"desc\"}],\"limit\":1}")' --query

3. Read the result

candid

type Value  = variant { null_; bool : bool; nat : nat; int : int; float : float; text : text };
type Cell   = record { name : text; value : Value };
type Result = record { rows : vec vec Cell; hasMore : bool };

The outer

rows = vec { ... }

is the row list; each inner

vec { ... }

is one row. Each

record { value = variant { "<tag>" = <payload> }; name = "<field>" }

is one cell —

name

tells you which field, the

<tag>

tells you the scalar type, the payload is the value.

35_000 : nat

underscores are digit separators — strip them if parsing.

hasMore = false

⇒ you got every match;

hasMore = true

⇒ truncated, fetch the next page. Look cells up by

name

, not position — order shifts if

select

changes.

4. Walk edges (joins)

Forward (single-valued) relationships are one query: a dotted path crosses a declared edge, in any field position. Reverse (one-to-many) relationships stay two queries with the

in

pattern (§4.2).

4.1 Forward (child → parent): dotted paths

"<edgeField>.<targetField>"

reads through the edge server-side — in

where

groupBy

orderBy

aggregate.field

, and

select

. Project through an edge in one query:

bash

icp canister call backend execute '("{\"start\":\"customer\",\"where\":{\"eq\":{\"field\":\"companyName\",\"value\":\"Northstar Public\"}},\"select\":[\"companyName\",\"accountManager.name\",\"accountManager.office\"]}")' --query

Multi-hop chains work (

"manager.department.name"

, max 4 hops), and it composes with aggregation — "average revenue by the account manager's office" is one call:

bash

icp canister call backend execute '("{\"start\":\"customer\",\"groupBy\":[\"accountManager.office\"],\"aggregate\":[{\"fn\":\"avg\",\"field\":\"monthlyRevenueUsd\",\"as\":\"avg_mrr\"}],\"orderBy\":[{\"field\":\"avg_mrr\",\"dir\":\"desc\"}]}")' --query

Rules:

The head segment must be a field whose
```
role
```
is
```
{"edge": {"to": ... }}
```
in
```
schema()
```
— a dotted path into a non-edge field traps, even if its values look like foreign keys (traversal is schema-driven, not name-guessed). If the author didn't declare the edge, fall back to the two-query pattern below.
A null or dangling FK resolves the whole dotted path to
```
null
```
(left-join): the row fails every relation except
```
ne
```
, and projects the cell as
```
null
```
.
Aggregate from the many side. Cross-entity aggregates run over the start entity's rows:
```
avg
```
of
```
"department.budget"
```
from
```
employee
```
is employee-weighted. For per-department numbers, start from
```
department
```
— or group by the dotted path and aggregate start-entity fields.
Selecting the bare edge field (
```
"accountManager"
```
) still returns the FK scalar; there is no
```
.*
```
— name each target field you want.

4.2 Reverse (one parent → many children)

eq

for one parent primary key,

in

for a batch — on the edge field, with the target entity's primary-key values.

bash

icp canister call backend execute '("{\"start\":\"customer\",\"where\":{\"eq\":{\"field\":\"accountManager\",\"value\":\"daniel@helix.systems\"}},\"select\":[\"companyName\",\"monthlyRevenueUsd\"]}")' --query

When the parent condition is a plain predicate, you don't need the batch — it's a forward filter through the edge (§4.1). "All customers managed by anyone in the Berlin office" is one query:

bash

icp canister call backend execute '("{\"start\":\"customer\",\"where\":{\"eq\":{\"field\":\"accountManager.office\",\"value\":\"Berlin\"}},\"select\":[\"companyName\",\"monthlyRevenueUsd\"]}")' --query

The batch

in

pattern is required when the parent set needs its own query shape (top-N, ordered, paginated): collect the keys first, then

in

on the edge field. "Customers managed by the three most senior employees" is two queries:

bash

icp canister call backend execute '("{\"start\":\"employee\",\"orderBy\":[{\"field\":\"level\",\"dir\":\"desc\"}],\"limit\":3,\"select\":[\"email\"]}")' --query
# collect the three emails from the rows, then:
icp canister call backend execute '("{\"start\":\"customer\",\"where\":{\"in\":{\"field\":\"accountManager\",\"value\":[\"alex@helix.systems\",\"james@helix.systems\",\"sarah@helix.systems\"]}},\"select\":[\"companyName\",\"monthlyRevenueUsd\"]}")' --query

Always batch with

in

rather than running N separate

eq

queries.

4.3 Compound conditions

Stack with

and

or

bash

icp canister call backend execute '("{\"start\":\"customer\",\"where\":{\"and\":[{\"eq\":{\"field\":\"plan\",\"value\":\"enterprise\"}},{\"in\":{\"field\":\"country\",\"value\":[\"US\",\"CA\",\"DE\"]}},{\"ge\":{\"field\":\"monthlyRevenueUsd\",\"value\":20000}}]},\"orderBy\":[{\"field\":\"monthlyRevenueUsd\",\"dir\":\"desc\"}]}")' --query

4.4 Two-hop / self-edge join

When the parent key isn't given but must be looked up first — e.g. "who reports to the lead of project

forge20

?" — run two queries. The second filters on a self-edge (

employee.manager

→

employee

) by the key the first query returned:

bash

icp canister call backend execute '("{\"start\":\"project\",\"where\":{\"eq\":{\"field\":\"codename\",\"value\":\"forge20\"}},\"select\":[\"lead\"]}")' --query
# the row's `lead` cell is the lead's email, e.g. priya@helix.systems — use it as the parent key:
icp canister call backend execute '("{\"start\":\"employee\",\"where\":{\"eq\":{\"field\":\"manager\",\"value\":\"priya@helix.systems\"}},\"select\":[\"name\",\"jobTitle\",\"level\"]}")' --query

5. Pagination

limit

caps results.

hasMore

reports truncation. Walk pages with

offset

text

offset = 0
limit  = 25
loop:
  result = icp canister call backend execute '("{\"start\":\"...\",\"limit\":25,\"offset\":<offset>,...}")' --query
  consume result.rows
  if not result.hasMore: break
  offset += limit

Always set

limit

explicitly. OQL itself imposes no cap (omitting

limit

returns every match), and a canister author may add one — in which case over-asking is silently truncated.

6. Pitfalls

Symptom	Cause / Fix
`execute` traps `OQL: unknown entity '...'`	`start` doesn't match any `name` from `schema()` — entity names are case-sensitive. Re-read the schema.
`execute` traps with a parse error	The JSON was malformed (trailing comma, single quotes), or not escaped as a Candid text literal — wrap as `("...")` with every inner `"` escaped as `\"` . Validate the JSON with `python3 -m json.tool` first.
No rows returned for a filter you expect to match	(1) `value` literal type doesn't match the field's `typeName` ( `"5"` for a `Nat` ); (2) typo in `field` — unknown fields are silently `null_` , so most predicates fail; (3) the field is genuinely `null_` in storage.
`gt` / `lt` returns weird results across types	Mixed-type comparisons aren't defined. Make sure both operands are the same `typeName` .
`contains` misses rows you can see	`contains` / `startsWith` / `endsWith` are case-sensitive. Use `icontains` for user-typed search terms.
Dotted path traps `'x' is not an edge of 'y'`	The head segment isn't a declared edge — traversal is schema-driven even when values look like FKs. Use the two-query `in` pattern instead.
Cross-entity average looks wrong	Aggregates run over the start entity's rows. Start from the entity whose rows you want averaged, or group by the dotted path and aggregate start-entity fields.
`execute` returns rows but missing fields	A field you `select` -ed isn't in the entity (typo, or hidden by the author). Drop it from `select` , or remove `select` for the default projection.

There is no structured error envelope. Any failure is a trap — fix the query and retry.

extension-querying-oql

NPX Install

Tags

SKILL.md Content

Querying OQL — quick reference

Calling the canister

Recipe

1. Discover —
`schema`

2. Form a query —
`execute`

2.1 Predicate operators

2.2 Aggregate — count, groupBy, sum/avg/min/max

3. Read the result

4. Walk edges (joins)

4.1 Forward (child → parent): dotted paths

4.2 Reverse (one parent → many children)

4.3 Compound conditions

4.4 Two-hop / self-edge join

5. Pagination

6. Pitfalls