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feat: kafka schema registry integration (#1959)
Signed-off-by: Farbod Ahmadian <farbodahmadian2014@gmail.com>
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181
databuilder/databuilder/extractor/kafka_schema_registry_extractor.py
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,181 @@ | ||
| # Copyright Contributors to the Amundsen project. | ||
| # SPDX-License-Identifier: Apache-2.0 | ||
| import logging | ||
| from asyncio.log import logger | ||
| from typing import ( | ||
| Any, Dict, Iterator, List, Optional, Union, | ||
| ) | ||
|
|
||
| from pyhocon import ConfigTree | ||
| from schema_registry.client import Auth, SchemaRegistryClient | ||
| from schema_registry.client.utils import SchemaVersion | ||
|
|
||
| from databuilder.extractor.base_extractor import Extractor | ||
| from databuilder.models.table_metadata import ColumnMetadata, TableMetadata | ||
|
|
||
| LOGGER = logging.getLogger(__name__) | ||
|
|
||
|
|
||
| class KafkaSchemaRegistryExtractor(Extractor): | ||
| """ | ||
| Extracts the latest version of all schemas from a given | ||
| Kafka Schema Registry URL | ||
| """ | ||
|
|
||
| REGISTRY_URL_KEY = "registry_url" | ||
| REGISTRY_USERNAME_KEY = "registry_username" | ||
| REGISTRY_PASSWORD_KEY = "registry_password" | ||
|
|
||
| def init(self, conf: ConfigTree) -> None: | ||
| self._registry_base_url = conf.get( | ||
| KafkaSchemaRegistryExtractor.REGISTRY_URL_KEY | ||
| ) | ||
|
|
||
| self._registry_username = conf.get( | ||
| KafkaSchemaRegistryExtractor.REGISTRY_USERNAME_KEY, None | ||
| ) | ||
|
|
||
| self._registry_password = conf.get( | ||
| KafkaSchemaRegistryExtractor.REGISTRY_PASSWORD_KEY, None | ||
| ) | ||
|
|
||
| # Add authentication if user and password are provided | ||
| if all((self._registry_username, self._registry_password)): | ||
| self._client = SchemaRegistryClient( | ||
| url=self._registry_base_url, | ||
| auth=Auth( | ||
| username=self._registry_username, | ||
| password=self._registry_password | ||
| ) | ||
| ) | ||
| else: | ||
| self._client = SchemaRegistryClient( | ||
| url=self._registry_base_url, | ||
| ) | ||
|
|
||
| self._extract_iter: Union[None, Iterator] = None | ||
|
|
||
| def extract(self) -> Union[TableMetadata, None]: | ||
| if not self._extract_iter: | ||
| self._extract_iter = self._get_extract_iter() | ||
| try: | ||
| return next(self._extract_iter) | ||
| except StopIteration: | ||
| return None | ||
| except Exception as e: | ||
| logger.error(f'Failed to generate next table: {e}') | ||
| return None | ||
|
|
||
| def get_scope(self) -> str: | ||
| return 'extractor.kafka_schema_registry' | ||
|
|
||
| def _get_extract_iter(self) -> Optional[Iterator[TableMetadata]]: | ||
| """ | ||
| Return an iterator generating TableMetadata for all of the schemas. | ||
| """ | ||
| for schema_version in self._get_raw_extract_iter(): | ||
| subject = schema_version.subject | ||
| schema = schema_version.schema.raw_schema | ||
| LOGGER.info((f'Subject: {subject}, ' | ||
| f'Schema: {schema}')) | ||
|
|
||
| try: | ||
| yield KafkaSchemaRegistryExtractor._create_table( | ||
| schema=schema, | ||
| subject_name=subject, | ||
| cluster_name=schema.get( | ||
| 'namespace', 'kafka-schema-registry' | ||
| ), | ||
| schema_name=schema.get('name', ''), | ||
| schema_description=schema.get('doc', None), | ||
| ) | ||
| except Exception as e: | ||
| logger.warning(f'Failed to generate table for {subject}: {e}') | ||
| continue | ||
|
|
||
| def _get_raw_extract_iter(self) -> Iterator[SchemaVersion]: | ||
| """ | ||
| Return iterator of results row from schema registry | ||
| """ | ||
| subjects = self._client.get_subjects() | ||
|
|
||
| LOGGER.info(f'Number of extracted subjects: {len(subjects)}') | ||
| LOGGER.info(f'Extracted subjects: {subjects}') | ||
|
|
||
| for subj in subjects: | ||
| subj_schema = self._client.get_schema(subj) | ||
| LOGGER.info(f'Subject <{subj}> max version: {subj_schema.version}') | ||
|
|
||
| yield subj_schema | ||
|
|
||
| @staticmethod | ||
| def _create_table( | ||
| schema: Dict[str, Any], | ||
| subject_name: str, | ||
| cluster_name: str, | ||
| schema_name: str, | ||
| schema_description: str, | ||
| ) -> Optional[TableMetadata]: | ||
| """ | ||
| Create TableMetadata based on given schema and names | ||
| """ | ||
| columns: List[ColumnMetadata] = [] | ||
|
|
||
| for i, field in enumerate(schema['fields']): | ||
| columns.append( | ||
| ColumnMetadata( | ||
| name=field['name'], | ||
| description=field.get('doc', None), | ||
| col_type=KafkaSchemaRegistryExtractor._get_property_type( | ||
| field | ||
| ), | ||
| sort_order=i, | ||
| ) | ||
| ) | ||
|
|
||
| return TableMetadata( | ||
| database='kafka_schema_registry', | ||
| cluster=cluster_name, | ||
| schema=subject_name, | ||
| name=schema_name, | ||
| description=schema_description, | ||
| columns=columns, | ||
| ) | ||
|
|
||
| @staticmethod | ||
| def _get_property_type(schema: Dict) -> str: | ||
| """ | ||
| Return type of the given schema. | ||
| It will also works for nested schema types. | ||
| """ | ||
| if 'type' not in schema: | ||
| return 'object' | ||
|
|
||
| if type(schema['type']) is dict: | ||
| return KafkaSchemaRegistryExtractor._get_property_type( | ||
| schema['type'] | ||
| ) | ||
|
|
||
| # If schema can have multiple types | ||
| if type(schema['type']) is list: | ||
| return '|'.join(schema['type']) | ||
|
|
||
| if schema['type'] == 'record': | ||
| properties = [ | ||
| f"{field['name']}:" | ||
| f"{KafkaSchemaRegistryExtractor._get_property_type(field)}" | ||
| for field in schema.get('fields', {}) | ||
| ] | ||
| if len(properties) > 0: | ||
| if 'name' in schema: | ||
| return schema['name'] + \ | ||
| ':struct<' + ','.join(properties) + '>' | ||
| return 'struct<' + ','.join(properties) + '>' | ||
| return 'struct<object>' | ||
| elif schema['type'] == 'array': | ||
| items = KafkaSchemaRegistryExtractor._get_property_type( | ||
| schema.get("items", {}) | ||
| ) | ||
| return 'array<' + items + '>' | ||
| else: | ||
| return schema['type'] |
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