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The two Function pages declare `launch: functions`, and every other page marks what it says about Functions, so the assembled site leaves them out until the launch. Before it, the pages that offered Functions for Python work point Enterprise readers at Geneva instead. The SQL Function example now uses Arrow type names, which the server requires, and states the 3.12 default for `python_version`.
203 lines
6.7 KiB
Plaintext
203 lines
6.7 KiB
Plaintext
---
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title: "Database"
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sidebarTitle: "Database"
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description: "Connecting to LanceDB: the URI forms, their options, and what each one changes."
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icon: database
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keywords: ["connect", "database", "uri", "api key", "storage options", "consistency"]
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availability:
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oss: available
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enterprise: available
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summary: >-
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The embedded library connects to a local directory or object storage, and
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a `db://` URI connects to a deployment. Which operations exist depends on
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the connection.
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---
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A database is the root of a [catalog](/basics/catalog). A connection opens
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exactly one, and every other object is reached through it.
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Connecting is the one decision that reaches furthest: the URI you pass decides
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where queries execute, which features exist, and what a table handle actually
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is.
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## The three URI forms {#uris}
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<CodeGroup>
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```python Python icon="python"
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import lancedb
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db = lancedb.connect("./.lancedb") # local directory
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db = lancedb.connect("s3://bucket/path") # object storage
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db = lancedb.connect("db://my-database", api_key="...") # a deployment
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```
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```typescript TypeScript icon="square-js"
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import * as lancedb from "@lancedb/lancedb";
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const db = await lancedb.connect("./.lancedb");
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const db = await lancedb.connect("s3://bucket/path");
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const db = await lancedb.connect("db://my-database", { apiKey: "..." });
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```
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</CodeGroup>
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The first two are **embedded**: your process opens Lance tables directly from
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storage and does the work itself. The third talks to a **deployment**.
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| | Embedded | Deployment |
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| --- | --- | --- |
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| Where queries run | in your process | on the server |
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| Table handle | `LanceTable` | `RemoteTable` |
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| [SQL](/basics/sql) | -- | where enabled |
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| Server-side [jobs](/basics/jobs) | -- | yes |
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| [Functions](/management/function) {/* if functions launched */} | -- | where enabled |
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| [Authorization](/governance/authorization) | storage permissions | granted per object, where configured |
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Both handles expose the same table API -- create, open, mutate, query -- so
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application code moves between them by changing the URI. What differs is where
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resolution and execution happen, and therefore which operations exist at all.
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## Connecting to a deployment {#deployment}
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<Badge color="red">Enterprise</Badge>
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<CodeGroup>
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```python Python icon="python"
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db = lancedb.connect(
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"db://my-database",
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api_key="...",
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region="us-east-1",
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)
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```
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```typescript TypeScript icon="square-js"
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const db = await lancedb.connect("db://my-database", {
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apiKey: "...",
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region: "us-east-1",
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});
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```
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</CodeGroup>
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| Option | Meaning |
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| --- | --- |
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| `api_key` / `apiKey` | authenticates the connection -- see [Authentication](/enterprise/authentication) |
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| `region` | which region hosts the database. Defaults to `us-east-1` |
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| `host_override` / `hostOverride` | point at a specific endpoint instead of the regional one |
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| `sql_host_override` | the same, for the [SQL endpoint](/sql#connecting). Python only |
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| `client_config` / `clientConfig` | retries, timeouts, and connection pooling |
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An API key belongs in the environment, not in source. `region` is easy to get
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wrong silently -- the default is `us-east-1` whether or not that is where your
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database lives, and a wrong region fails as a connection error rather than a
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helpful one.
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## Storage options {#storage-options}
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`storage_options` configures the underlying object store -- credentials,
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endpoints, and defaults for tables created through this connection:
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<CodeGroup>
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```python Python icon="python"
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db = lancedb.connect(
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"s3://bucket/path",
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storage_options={"new_table_enable_stable_row_ids": "true"},
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)
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```
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```typescript TypeScript icon="square-js"
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const db = await lancedb.connect("s3://bucket/path", {
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storageOptions: { new_table_enable_stable_row_ids: "true" },
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});
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```
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</CodeGroup>
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<Warning>
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`new_table_enable_stable_row_ids` is worth setting deliberately: it gives stable
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row ids to the tables this connection creates, and no SDK call adds them to an
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existing table. A `db://` connection does not send it; a deployment decides
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stable row ids itself (see
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[Against a deployment](/feature-engineering/materialized-views#availability)).
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</Warning>
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See [Storage](/deployment/storage) for the full set, including per-cloud credentials.
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## Read consistency {#consistency}
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`read_consistency_interval` controls how often a connection checks for versions
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committed by other writers.
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<CodeGroup>
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```python Python icon="python"
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from datetime import timedelta
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db = lancedb.connect(uri, read_consistency_interval=timedelta(seconds=5))
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```
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```typescript TypeScript icon="square-js"
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const db = await lancedb.connect(uri, { readConsistencyInterval: 5 });
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```
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</CodeGroup>
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In the embedded library, the default reads a snapshot taken when the table was
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opened, so a long-lived connection **will not see other processes' writes**
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until it reopens the table. That is the right default for a batch job and the
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wrong one for a service. On a deployment, reads follow the deployment's own
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freshness setting, which the interval can only tighten.
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Set it when several processes write the same table and readers must observe
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those writes. The cost is a metadata check on that interval. See
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[Consistency](/tables/consistency).
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## Database-level operations {#operations}
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| | Python | TypeScript | SQL |
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| --- | --- | --- | --- |
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| list tables | `table_names`, `list_tables` | `tableNames`, `listTables` | -- |
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| the URI it opened | `uri` | `display()` | -- |
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| drop every table, embedded only | `drop_all_tables` | `dropAllTables` | -- |
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| drop the database, embedded only | `drop_database` | -- | -- |
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| close | -- | `close`, `isOpen` | -- |
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<CodeGroup>
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```python Python icon="python"
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db.table_names()
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tbl = db.open_table("documents")
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db.drop_table("documents")
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```
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```typescript TypeScript icon="square-js"
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await db.tableNames();
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const tbl = await db.openTable("documents");
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await db.dropTable("documents");
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```
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```sql SQL
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DROP TABLE documents;
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```
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</CodeGroup>
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Each takes a `namespace_path` to act inside a [namespace](/management/namespace) rather
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than at the root.
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<Warning>
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`drop_database()` removes every table in the database. There is no confirmation
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and no undo -- table [versioning](/management/table#versioning) does not survive the table
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being dropped.
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</Warning>
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## Async connections {#async}
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`connect_async` returns an `AsyncConnection` with the same surface as
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coroutines. The TypeScript SDK is async throughout, so its `connect` already is
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one.
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```python
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db = await lancedb.connect_async("db://my-database", api_key="...")
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tbl = await db.open_table("documents")
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```
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This is a different axis from the `_async` operations that return a
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[job](/basics/jobs): `connect_async` is about not blocking your event loop,
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while `create_index_async` is about work that outlives the call.
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