def create_or_replace_stitch_view(
        bigquery_client,
        dataset_name,
        table_definition,
        ds,
        destination_project_id,
        internal_project_id,
        sqls_folder
):
    table_name = table_definition['table']['table_name']
    history_table_name = table_name + '_history'

    # # # Create view

    sql = render_stitch_view_template(
        sqls_folder=sqls_folder,
        internal_project_id=internal_project_id,
        dataset_name=dataset_name,
        table_name=table_name,
        history_table_name=history_table_name,
        ds=ds
    )

    print('Stitch view: ' + sql)

    dataset = create_dataset(bigquery_client, dataset_name, destination_project_id)
    dest_view_ref = dataset.table(table_name)

    create_view(bigquery_client, sql, dest_view_ref)
Beispiel #2
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        def create_view_task(ds, **kwargs):
            client = bigquery.Client()

            dest_table_name = view_name
            dest_table_ref = create_dataset(client, dataset_name, parse_destination_dataset_project_id).table(dest_table_name)

            print('View sql: \n' + sql)

            create_view(client, sql, dest_table_ref)
def create_or_replace_internal_view(bigquery_client, dataset_name,
                                    table_definition, ds, public_project_id,
                                    public_dataset_name, internal_project_id,
                                    destination_project_id, sqls_folder):
    table_name = table_definition['table']['table_name']

    parser_type = table_definition['parser'].get('type', 'log')

    udf_name = 'parse_{}'.format(table_name)

    dataset = create_dataset(bigquery_client, dataset_name,
                             internal_project_id)

    # # # Create UDF

    sql = render_parse_udf_template(
        sqls_folder,
        parser_type,
        internal_project_id=internal_project_id,
        dataset_name=dataset_name,
        udf_name=udf_name,
        abi=json.dumps(table_definition['parser']['abi']),
        struct_fields=create_struct_string_from_schema(
            table_definition['table']['schema']))
    query(bigquery_client, sql)

    # # # Create view

    selector = abi_to_selector(parser_type, table_definition['parser']['abi'])

    parse_mode = get_parse_mode(HistoryType.LIVE)
    full_source_table_name = get_source_table(
        parser_type=parser_type,
        parse_mode=parse_mode,
        ds=ds,
        internal_project_id=internal_project_id,
        public_project_id=public_project_id,
        public_dataset_name=public_dataset_name,
        selector=selector)

    sql = generate_parse_sql_template(
        sqls_folder,
        parser_type,
        parse_mode,
        full_source_table_name=full_source_table_name,
        selector=selector,
        internal_project_id=internal_project_id,
        destination_project_id=destination_project_id,
        dataset_name=dataset_name,
        udf_name=udf_name,
        table_definition=table_definition,
        parse_all_partitions=None,
        ds=ds)

    dest_view_ref = dataset.table(table_name)
    create_view(bigquery_client, sql, dest_view_ref)
        def create_view_task(ds, **kwargs):

            client = bigquery.Client()

            dest_table_name = 'amended_tokens'
            dest_table_ref = client.dataset(dataset_name, project=destination_dataset_project_id).table(dest_table_name)

            sql_path = os.path.join(dags_folder, 'resources/stages/enrich/sqls/amended_tokens.sql')
            sql = read_file(sql_path)
            print('amended_tokens view: \n' + sql)

            description = 'Tokens amended with data from https://github.com/blockchain-etl/ethereum-etl-airflow/blob/master/dags/resources/stages/seed/data/token_amendments.csv'
            create_view(client, sql, dest_table_ref, description=description)