postgres version of sample_dag for amundsen databuilder

postgres_sample_dag.py

import logging
import textwrap
from datetime import datetime, timedelta
import uuid

from elasticsearch import Elasticsearch
from airflow import DAG  # noqa
from airflow import macros  # noqa
from airflow.operators.python_operator import PythonOperator  # noqa
from pyhocon import ConfigFactory
from databuilder.extractor.neo4j_search_data_extractor import Neo4jSearchDataExtractor
from databuilder.extractor.postgres_table_metadata_extractor import PostgresTableMetadataExtractor
from databuilder.extractor.sql_alchemy_extractor import SQLAlchemyExtractor
from databuilder.publisher.elasticsearch_publisher import ElasticsearchPublisher
from databuilder.extractor.neo4j_extractor import Neo4jExtractor
from databuilder.job.job import DefaultJob
from databuilder.models.table_metadata import DESCRIPTION_NODE_LABEL
from databuilder.loader.file_system_elasticsearch_json_loader import FSElasticsearchJSONLoader
from databuilder.loader.file_system_neo4j_csv_loader import FsNeo4jCSVLoader
from databuilder.publisher import neo4j_csv_publisher
from databuilder.publisher.neo4j_csv_publisher import Neo4jCsvPublisher
from databuilder.task.task import DefaultTask
from databuilder.transformer.base_transformer import NoopTransformer
from databuilder.transformer.elasticsearch_document_transformer import ElasticsearchDocumentTransformer
from databuilder import Scoped


dag_args = {
    'concurrency': 10,
    # One dagrun at a time
    'max_active_runs': 1,
    # 4AM, 4PM PST
    'schedule_interval': '0 11 * * *',
    'catchup': False
}

default_args = {
    'owner': 'amundsen',
    'start_date': datetime(2018, 6, 18),
    'depends_on_past': False,
    'email': [''],
    'email_on_failure': False,
    'email_on_retry': False,
    'retries': 3,
    'priority_weight': 10,
    'retry_delay': timedelta(minutes=5),
    'execution_timeout': timedelta(minutes=120)
}

# NEO4J cluster endpoints
NEO4J_ENDPOINT = 'bolt://neo4j:7687'

neo4j_endpoint = NEO4J_ENDPOINT

neo4j_user = 'neo4j'
neo4j_password = 'test'

es = Elasticsearch([
    {'host': 'elasticsearch'},
])


# Todo: user needs to modify and provide a hivemetastore connection string
def connection_string():
    return 'postgresql://jstanfield:testtest@host.docker.internal:5433/moviesdemo'


def create_table_extract_job(**kwargs):
    where_clause_suffix = textwrap.dedent("""
        where table_name='movies'
        and table_catalog='moviesdemo' and table_schema='moviesdemo'
    """)

    tmp_folder = '/var/tmp/amundsen/table_metadata'
    node_files_folder = '{tmp_folder}/nodes/'.format(tmp_folder=tmp_folder)
    relationship_files_folder = '{tmp_folder}/relationships/'.format(tmp_folder=tmp_folder)

    job_config = ConfigFactory.from_dict({
        'extractor.postgres_table_metadata.{}'.format(PostgresTableMetadataExtractor.WHERE_CLAUSE_SUFFIX_KEY):
            where_clause_suffix,
        'extractor.postgres_table_metadata.extractor.sqlalchemy.{}'.format(SQLAlchemyExtractor.CONN_STRING):
            connection_string(),
        'loader.filesystem_csv_neo4j.{}'.format(FsNeo4jCSVLoader.NODE_DIR_PATH):
            node_files_folder,
        'loader.filesystem_csv_neo4j.{}'.format(FsNeo4jCSVLoader.RELATION_DIR_PATH):
            relationship_files_folder,
        'publisher.neo4j.{}'.format(neo4j_csv_publisher.NODE_FILES_DIR):
            node_files_folder,
        'publisher.neo4j.{}'.format(neo4j_csv_publisher.RELATION_FILES_DIR):
            relationship_files_folder,
        'publisher.neo4j.{}'.format(neo4j_csv_publisher.NEO4J_END_POINT_KEY):
            neo4j_endpoint,
        'publisher.neo4j.{}'.format(neo4j_csv_publisher.NEO4J_USER):
            neo4j_user,
        'publisher.neo4j.{}'.format(neo4j_csv_publisher.NEO4J_PASSWORD):
            neo4j_password,
        'publisher.neo4j.{}'.format(neo4j_csv_publisher.JOB_PUBLISH_TAG):
            'unique_tag',  # should use unique tag here like {ds}
    })
    job = DefaultJob(conf=job_config,
                     task=DefaultTask(extractor=PostgresTableMetadataExtractor(), loader=FsNeo4jCSVLoader()),
                     publisher=Neo4jCsvPublisher())
    job.launch()


def create_es_publisher_sample_job():

    # loader save data to this location and publisher read if from here
    extracted_search_data_path = '/var/tmp/amundsen/search_data.json'

    task = DefaultTask(loader=FSElasticsearchJSONLoader(),
                       extractor=Neo4jSearchDataExtractor(),
                       transformer=ElasticsearchDocumentTransformer())

    # elastic search client instance
    elasticsearch_client = es
    # unique name of new index in Elasticsearch
    elasticsearch_new_index_key = 'tables' + str(uuid.uuid4())
    # related to mapping type from /databuilder/publisher/elasticsearch_publisher.py#L38
    elasticsearch_new_index_key_type = 'table'
    # alias for Elasticsearch used in amundsensearchlibrary/search_service/config.py as an index
    elasticsearch_index_alias = 'table_search_index'

    job_config = ConfigFactory.from_dict({
        'extractor.search_data.extractor.neo4j.{}'.format(Neo4jExtractor.GRAPH_URL_CONFIG_KEY): neo4j_endpoint,
        'extractor.search_data.extractor.neo4j.{}'.format(Neo4jExtractor.MODEL_CLASS_CONFIG_KEY):
            'databuilder.models.neo4j_data.Neo4jDataResult',
        'extractor.search_data.extractor.neo4j.{}'.format(Neo4jExtractor.NEO4J_AUTH_USER): neo4j_user,
        'extractor.search_data.extractor.neo4j.{}'.format(Neo4jExtractor.NEO4J_AUTH_PW): neo4j_password,
        'loader.filesystem.elasticsearch.{}'.format(FSElasticsearchJSONLoader.FILE_PATH_CONFIG_KEY):
            extracted_search_data_path,
        'loader.filesystem.elasticsearch.{}'.format(FSElasticsearchJSONLoader.FILE_MODE_CONFIG_KEY): 'w',
        'transformer.elasticsearch.{}'.format(ElasticsearchDocumentTransformer.ELASTICSEARCH_INDEX_CONFIG_KEY):
            elasticsearch_new_index_key,
        'transformer.elasticsearch.{}'.format(ElasticsearchDocumentTransformer.ELASTICSEARCH_DOC_CONFIG_KEY):
            elasticsearch_new_index_key_type,
        'publisher.elasticsearch.{}'.format(ElasticsearchPublisher.FILE_PATH_CONFIG_KEY):
            extracted_search_data_path,
        'publisher.elasticsearch.{}'.format(ElasticsearchPublisher.FILE_MODE_CONFIG_KEY): 'r',
        'publisher.elasticsearch.{}'.format(ElasticsearchPublisher.ELASTICSEARCH_CLIENT_CONFIG_KEY):
            elasticsearch_client,
        'publisher.elasticsearch.{}'.format(ElasticsearchPublisher.ELASTICSEARCH_NEW_INDEX_CONFIG_KEY):
            elasticsearch_new_index_key,
        'publisher.elasticsearch.{}'.format(ElasticsearchPublisher.ELASTICSEARCH_ALIAS_CONFIG_KEY):
            elasticsearch_index_alias
    })

    job = DefaultJob(conf=job_config,
                     task=task,
                     publisher=ElasticsearchPublisher())
    job.launch()

with DAG('amundsen_databuilder', default_args=default_args, **dag_args) as dag:

    create_table_extract_job = PythonOperator(
        task_id='create_table_extract_job',
        python_callable=create_table_extract_job
    )

    create_es_index_job = PythonOperator(
        task_id='create_es_publisher_sample_job',
        python_callable=create_es_publisher_sample_job
    )