Apache Hive
Apache Hive
Scan Hive tables and views across selected databases.
- Category
- Warehouse & Lakehouse
- Source type
- HIVE
- Produces
- table
Hive is the SQL layer over Hadoop-era data lakes, and the metastore behind a lot of Spark platforms. Where it’s still running, it usually holds the oldest and least-governed data in the estate.
What you need to connect
Host and port for HiveServer2, plus a username and password. The transport scheme is a setting: native binary, HTTP, HTTPS, Spark SQL, or the Databricks flavour. Anything else the driver needs — Kerberos service name, an HTTP path — goes in the extra connection arguments.
What Classifyre reads
Tables and views, in one database or across all visible databases, with a denylist for the ones you don’t want and an object allowlist for the ones you do.
Shared behaviour · SQL databases
One asset per table or view, never one per row. The asset carries the table's structure — database, schema, table name, object type, its columns and their types, and a row-count estimate — and its content is a sample of real rows, formatted so a detector reads actual values rather than a schema dump.
How many rows, and which ones, is entirely up to the sampling strategy. Large tables are paged through by key rather than by OFFSET, so a scan that stops halfway can resume from where it left off instead of re-reading from the top.
Read-only throughout. The connector issues catalog queries and bounded SELECTs. Nothing is written back, and a read-only account is the right account to give it.
Relationships come out of the engine's own catalog: a view and the tables it reads from are recorded as FLOW — real lineage, with column-level detail parsed out of the view's SQL where the SQL makes that possible. See Lineage.
Metadata on every asset
Asset kind · table
| Field | Type | Always present | What it is |
|---|---|---|---|
| database | string | Yes | Database or catalog name |
| table_name | string | Yes | Table name |
| table_type | string | Yes | Object type (TABLE/VIEW) |
| schema | string | No | Schema name |
| columns | object[] | No | Columns as {name, type} objects |
| row_count | integer | No | Estimated number of rows |
| object_type | string | No | Source object type |
Lineage
Lineage
Views and the tables they read are recovered from the metastore and recorded as lineage, with column detail parsed from the view SQL where it can be. Hive has no enforced foreign keys, so there are no reference edges to record. See Lineage & Relationships.
Worth knowing
- Row counts come from table statistics where they exist. Tables that have never been analysed report no estimate rather than a wrong one.
- Spark SQL endpoints connect through the same source — pick the Spark SQL scheme.
Configuration
Beyond the fields below, every source also has the settings shared by all of them: the sampling strategy, the detectors to run, the scan schedule, and the compute limits for its scan jobs.
Required
Without these, the source will not save.
| Field | Type | Required | What it does | Default |
|---|---|---|---|---|
| required | object | Yes | —no extra properties | — |
| host | string | Yes | Hive host endpoint | localhost |
| port | integer | Yes | Hive TCP portmin 1, max 65535 | 10000 |
Secrets
Stored encrypted and never shown again after you save them. See Configuration & Fields.
| Field | Type | Required | What it does | Default |
|---|---|---|---|---|
| masked | object | Yes | —no extra properties | — |
| password | string | Yes | Hive login password | — |
| username | string | Yes | Hive login username | — |
Optional
Everything you can tune. Sensible defaults apply when you leave them alone.
| Field | Type | Required | What it does | Default |
|---|---|---|---|---|
| optional | object | No | —no extra properties | — |
| connection | object | No | Hive connection transport and authentication options.no extra properties | — |
| connection.connect_args | object | No | Additional PyHive connection arguments (e.g. auth, kerberos_service_name, http_path). | {} |
| connection.scheme | enum | No | Hive transport and driver scheme Allowed: hive, hive+http, hive+https, sparksql, databricks+pyhive | — |
| scope | object | No | Hive database and object selection scope.no extra properties | — |
| scope.database | string | No | Single Hive database to scan (optional when include_all_databases is true) | — |
| scope.exclude_databases | array | No | Database denylist (exact database names) | ["information_schema","sys"] |
| scope.exclude_databases[] | string | No | — | — |
| scope.include_all_databases | boolean | No | Scan all visible Hive databases except excluded system databases | false |
| scope.include_objects | array | No | Optional object allowlist. Accepted forms: table or database.table | — |
| scope.include_objects[] | string | No | — | — |
| scope.include_tables | boolean | No | Include table assets in extraction | true |
| scope.include_views | boolean | No | Include view assets in extraction | true |
| scope.table_limit | integer | No | Optional cap on number of table/view assets extracted per databasemin 1 | — |