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The Hive adapter plugin for dbt

Project description

dbt-hive

The dbt-hive adapter allows you to use dbt along with Apache Hive and Cloudera Data Platform

Getting started

Credits

The initial adapter code was developed by bachng2017 who agreed to transfer the ownership and continue active development. This code base is now being actively developed and maintained by Cloudera.

Requirements

Current version of dbt-hive use dbt-core 1.4.*. We are actively working on supporting the next version of dbt-core 1.5

Python >= 3.8 dbt-core ~= 1.4.* impyla >= 0.18

Install

pip3 install --user dbt-hive

Sample profile

demo_project:
  target: dev
  outputs:
  dev:
    type: hive
    auth_type: LDAP
    user: [username]
    password: [password]
    schema: [schema]
    host: [hive-meta-store-host]
    port: 443
    http_path: [http-path]
    thread: 1

Supported features

Name Supported Iceberg
Materialization: View Yes N/A
Materialization: Table Yes Yes
Materialization: Table with Partitions Yes Yes
Materialization: Incremental - Append Yes Yes
Materialization: Incremental - Append with Partitions Yes Yes
Materialization: Incremental - Insert+Overwrite No No
Materialization: Incremental - Insert+Overwrite with Partitions Yes No
Materialization: Incremental - Merge No Yes
Materialization: Ephemeral No No
Seeds Yes Yes
Tests Yes Yes
Snapshots No No
Documentation Yes No
Authentication: LDAP Yes Yes
Authentication: Kerberos Yes Yes

Incremental

Incremental models are explained in dbt documentation. This section covered the details about the incremental strategy supported by the dbt-hive.

Strategy ACID Table Iceberg Table
Incremental Full-Refresh Yes Yes
Incremental Append Yes Yes
Incremental Append with Partitions Yes Yes
Incremental Insert Overwrite No No
Incremental Insert Overwrite with Partitions Yes No
Incremental Merge No Yes
Incremental Merge with Partitions No Yes

Support for On-Schema Change strategy in dbt-hive:

Strategy ACID Table Iceberg Table
ignore (default) Supported Supported
fail Supported Supported
append_new_columns Adds new columns Adds new columns
sync_all_columns Adds new columns and updates datatypes but doesn't remove existing columns Adds new columns, updates datatypes and removes existing columns

Tests Coverage

Functional Tests

Name Base Iceberg
Materialization: View Yes N/A
Materialization: Table Yes Yes
Materialization: Table with Partitions Yes Yes
Materialization: Incremental - Append Yes Yes
Materialization: Incremental - Append with Partitions Yes Yes
Materialization: Incremental - Insert+Overwrite Yes Yes
Materialization: Incremental - Insert+Overwrite with Partitions Yes Yes
Materialization: Incremental - Merge No No
Materialization: Ephemeral No No
Seeds Yes Yes
Tests Yes Yes
Snapshots No No
Documentation Yes No
Authentication: LDAP Yes Yes
Authentication: Kerberos Yes Yes

Note: Kerberos is only qualified on Unix platform.

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