Source code for airflow.operators.s3_to_hive_operator

# -*- coding: utf-8 -*-
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
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# http://www.apache.org/licenses/LICENSE-2.0
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from builtins import next
from builtins import zip
from tempfile import NamedTemporaryFile
from airflow.utils.file import TemporaryDirectory
import gzip
import bz2
import tempfile
import os

from airflow.exceptions import AirflowException
from airflow.hooks.S3_hook import S3Hook
from airflow.hooks.hive_hooks import HiveCliHook
from airflow.models import BaseOperator
from airflow.utils.decorators import apply_defaults
from airflow.utils.compression import uncompress_file


[docs]class S3ToHiveTransfer(BaseOperator): """ Moves data from S3 to Hive. The operator downloads a file from S3, 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 from. 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 tables 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 s3_key: The key to be retrieved from S3 :type s3_key: str :param field_dict: A dictionary of the fields name in the file as keys and their Hive types as values :type field_dict: dict :param hive_table: target Hive table, use dot notation to target a specific database :type hive_table: str :param create: whether to create the table if it doesn't exist :type create: bool :param recreate: whether to drop and recreate the table at every execution :type recreate: bool :param partition: target partition as a dict of partition columns and values :type partition: dict :param headers: whether the file contains column names on the first line :type headers: bool :param check_headers: whether the column names on the first line should be checked against the keys of field_dict :type check_headers: bool :param wildcard_match: whether the s3_key should be interpreted as a Unix wildcard pattern :type wildcard_match: bool :param delimiter: field delimiter in the file :type delimiter: str :param aws_conn_id: source s3 connection :type aws_conn_id: str :param hive_cli_conn_id: destination hive connection :type hive_cli_conn_id: str :param input_compressed: Boolean to determine if file decompression is required to process headers :type input_compressed: bool :param tblproperties: TBLPROPERTIES of the hive table being created :type tblproperties: dict """ template_fields = ('s3_key', 'partition', 'hive_table') template_ext = () ui_color = '#a0e08c' @apply_defaults def __init__( self, s3_key, field_dict, hive_table, delimiter=',', create=True, recreate=False, partition=None, headers=False, check_headers=False, wildcard_match=False, aws_conn_id='aws_default', hive_cli_conn_id='hive_cli_default', input_compressed=False, tblproperties=None, *args, **kwargs): super(S3ToHiveTransfer, self).__init__(*args, **kwargs) self.s3_key = s3_key self.field_dict = field_dict self.hive_table = hive_table self.delimiter = delimiter self.create = create self.recreate = recreate self.partition = partition self.headers = headers self.check_headers = check_headers self.wildcard_match = wildcard_match self.hive_cli_conn_id = hive_cli_conn_id self.aws_conn_id = aws_conn_id self.input_compressed = input_compressed self.tblproperties = tblproperties if (self.check_headers and not (self.field_dict is not None and self.headers)): raise AirflowException("To check_headers provide " + "field_dict and headers") def execute(self, context): # Downloading file from S3 self.s3 = S3Hook(aws_conn_id=self.aws_conn_id) self.hive = HiveCliHook(hive_cli_conn_id=self.hive_cli_conn_id) self.log.info("Downloading S3 file") if self.wildcard_match: if not self.s3.check_for_wildcard_key(self.s3_key): raise AirflowException("No key matches {0}" .format(self.s3_key)) s3_key_object = self.s3.get_wildcard_key(self.s3_key) else: if not self.s3.check_for_key(self.s3_key): raise AirflowException( "The key {0} does not exists".format(self.s3_key)) s3_key_object = self.s3.get_key(self.s3_key) root, file_ext = os.path.splitext(s3_key_object.key) with TemporaryDirectory(prefix='tmps32hive_') as tmp_dir,\ NamedTemporaryFile(mode="wb", dir=tmp_dir, suffix=file_ext) as f: self.log.info("Dumping S3 key {0} contents to local file {1}" .format(s3_key_object.key, f.name)) s3_key_object.download_fileobj(f) f.flush() if not self.headers: self.log.info("Loading file %s into Hive", f.name) self.hive.load_file( f.name, self.hive_table, field_dict=self.field_dict, create=self.create, partition=self.partition, delimiter=self.delimiter, recreate=self.recreate, tblproperties=self.tblproperties) else: # Decompressing file if self.input_compressed: self.log.info("Uncompressing file %s", f.name) fn_uncompressed = uncompress_file(f.name, file_ext, tmp_dir) self.log.info("Uncompressed to %s", fn_uncompressed) # uncompressed file available now so deleting # compressed file to save disk space f.close() else: fn_uncompressed = f.name # Testing if header matches field_dict if self.check_headers: self.log.info("Matching file header against field_dict") header_list = self._get_top_row_as_list(fn_uncompressed) if not self._match_headers(header_list): raise AirflowException("Header check failed") # Deleting top header row self.log.info("Removing header from file %s", fn_uncompressed) headless_file = ( self._delete_top_row_and_compress(fn_uncompressed, file_ext, tmp_dir)) self.log.info("Headless file %s", headless_file) self.log.info("Loading file %s into Hive", headless_file) self.hive.load_file(headless_file, self.hive_table, field_dict=self.field_dict, create=self.create, partition=self.partition, delimiter=self.delimiter, recreate=self.recreate, tblproperties=self.tblproperties) def _get_top_row_as_list(self, file_name): with open(file_name, 'rt') as f: header_line = f.readline().strip() header_list = header_line.split(self.delimiter) return header_list def _match_headers(self, header_list): if not header_list: raise AirflowException("Unable to retrieve header row from file") field_names = self.field_dict.keys() if len(field_names) != len(header_list): self.log.warning("Headers count mismatch" "File headers:\n {header_list}\n" "Field names: \n {field_names}\n" "".format(**locals())) return False test_field_match = [h1.lower() == h2.lower() for h1, h2 in zip(header_list, field_names)] if not all(test_field_match): self.log.warning("Headers do not match field names" "File headers:\n {header_list}\n" "Field names: \n {field_names}\n" "".format(**locals())) return False else: return True def _delete_top_row_and_compress( self, input_file_name, output_file_ext, dest_dir): # When output_file_ext is not defined, file is not compressed open_fn = open if output_file_ext.lower() == '.gz': open_fn = gzip.GzipFile elif output_file_ext.lower() == '.bz2': open_fn = bz2.BZ2File os_fh_output, fn_output = \ tempfile.mkstemp(suffix=output_file_ext, dir=dest_dir) with open(input_file_name, 'rb') as f_in,\ open_fn(fn_output, 'wb') as f_out: f_in.seek(0) next(f_in) for line in f_in: f_out.write(line) return fn_output