Source code for airflow.providers.apache.hive.transfers.vertica_to_hive

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"""This module contains an operator to move data from Vertica to Hive."""

from __future__ import annotations

import csv
from tempfile import NamedTemporaryFile
from typing import TYPE_CHECKING, Any, Sequence

from airflow.models import BaseOperator
from airflow.providers.apache.hive.hooks.hive import HiveCliHook
from airflow.providers.vertica.hooks.vertica import VerticaHook

    from airflow.utils.context import Context

[docs]class VerticaToHiveOperator(BaseOperator): """ Moves data from Vertica to Hive. The operator runs your query against Vertica, stores the file locally before loading it into a Hive table. If the ``create`` or ``recreate`` arguments are set to ``True``, a ``CREATE TABLE`` and ``DROP TABLE`` statements are generated. Hive data types are inferred from the cursor's metadata. Note that the table generated in Hive uses ``STORED AS textfile`` which isn't the most efficient serialization format. If a large amount of data is loaded and/or if the table gets queried considerably, you may want to use this operator only to stage the data into a temporary table before loading it into its final destination using a ``HiveOperator``. :param sql: SQL query to execute against the Vertica database. (templated) :param hive_table: target Hive table, use dot notation to target a specific database. (templated) :param create: whether to create the table if it doesn't exist :param recreate: whether to drop and recreate the table at every execution :param partition: target partition as a dict of partition columns and values. (templated) :param delimiter: field delimiter in the file :param vertica_conn_id: source Vertica connection :param hive_cli_conn_id: Reference to the :ref:`Hive CLI connection id <howto/connection:hive_cli>`. :param hive_auth: optional authentication option passed for the Hive connection """
[docs] template_fields: Sequence[str] = ("sql", "partition", "hive_table")
[docs] template_ext: Sequence[str] = (".sql",)
[docs] template_fields_renderers = {"sql": "sql"}
[docs] ui_color = "#b4e0ff"
def __init__( self, *, sql: str, hive_table: str, create: bool = True, recreate: bool = False, partition: dict | None = None, delimiter: str = chr(1), vertica_conn_id: str = "vertica_default", hive_cli_conn_id: str = "hive_cli_default", hive_auth: str | None = None, **kwargs: Any, ) -> None: super().__init__(**kwargs) self.sql = sql self.hive_table = hive_table self.partition = partition self.create = create self.recreate = recreate self.delimiter = str(delimiter) self.vertica_conn_id = vertica_conn_id self.hive_cli_conn_id = hive_cli_conn_id self.partition = partition or {} self.hive_auth = hive_auth @classmethod
[docs] def type_map(cls, vertica_type): """Manually hack Vertica-Python type mapping. The stock does not provide the full type mapping access. Reference: """ type_map = { 5: "BOOLEAN", 6: "INT", 7: "FLOAT", 8: "STRING", 9: "STRING", 16: "FLOAT", } return type_map.get(vertica_type, "STRING")
[docs] def execute(self, context: Context): hive = HiveCliHook(hive_cli_conn_id=self.hive_cli_conn_id, auth=self.hive_auth) vertica = VerticaHook(vertica_conn_id=self.vertica_conn_id)"Dumping Vertica query results to local file") conn = vertica.get_conn() cursor = conn.cursor() cursor.execute(self.sql) with NamedTemporaryFile(mode="w", encoding="utf-8") as f: csv_writer = csv.writer(f, delimiter=self.delimiter) field_dict = {} for col_count, field in enumerate(cursor.description, start=1): col_position = f"Column{col_count}" field_dict[col_position if field[0] == "" else field[0]] = self.type_map(field[1]) csv_writer.writerows(cursor.iterate()) f.flush() cursor.close() conn.close()"Loading file into Hive") hive.load_file(, self.hive_table, field_dict=field_dict, create=self.create, partition=self.partition, delimiter=self.delimiter, recreate=self.recreate, )

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