Source code for airflow.operators.s3_to_hive_operator

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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. (templated) :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. (templated) :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. (templated) :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 verify: Whether or not to verify SSL certificates for S3 connection. By default SSL certificates are verified. You can provide the following values: - ``False``: do not validate SSL certificates. SSL will still be used (unless use_ssl is False), but SSL certificates will not be verified. - ``path/to/cert/bundle.pem``: A filename of the CA cert bundle to uses. You can specify this argument if you want to use a different CA cert bundle than the one used by botocore. :type verify: bool or 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 :param select_expression: S3 Select expression :type select_expression: str """
[docs] template_fields = ('s3_key', 'partition', 'hive_table')
[docs] template_ext = ()
[docs] 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', verify=None, hive_cli_conn_id='hive_cli_default', input_compressed=False, tblproperties=None, select_expression=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.verify = verify self.input_compressed = input_compressed self.tblproperties = tblproperties self.select_expression = select_expression 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")
[docs] def execute(self, context): # Downloading file from S3 self.s3 = S3Hook(aws_conn_id=self.aws_conn_id, verify=self.verify) self.hive = HiveCliHook(hive_cli_conn_id=self.hive_cli_conn_id)"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) if (self.select_expression and self.input_compressed and file_ext.lower() != '.gz'): raise AirflowException("GZIP is the only compression " + "format Amazon S3 Select supports") with TemporaryDirectory(prefix='tmps32hive_') as tmp_dir,\ NamedTemporaryFile(mode="wb", dir=tmp_dir, suffix=file_ext) as f: "Dumping S3 key %s contents to local file %s", s3_key_object.key, ) if self.select_expression: option = {} if self.headers: option['FileHeaderInfo'] = 'USE' if self.delimiter: option['FieldDelimiter'] = self.delimiter input_serialization = {'CSV': option} if self.input_compressed: input_serialization['CompressionType'] = 'GZIP' content = self.s3.select_key( bucket_name=s3_key_object.bucket_name, key=s3_key_object.key, expression=self.select_expression, input_serialization=input_serialization ) f.write(content.encode("utf-8")) else: s3_key_object.download_fileobj(f) f.flush() if self.select_expression or not self.headers:"Loading file %s into Hive", self.hive.load_file(, 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:"Uncompressing file %s", fn_uncompressed = uncompress_file(, file_ext, tmp_dir)"Uncompressed to %s", fn_uncompressed) # uncompressed file available now so deleting # compressed file to save disk space f.close() else: fn_uncompressed = # Testing if header matches field_dict if self.check_headers:"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"Removing header from file %s", fn_uncompressed) headless_file = ( self._delete_top_row_and_compress(fn_uncompressed, file_ext, tmp_dir))"Headless file %s", headless_file)"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)
[docs] 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
[docs] 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 %s\nField names: \n %s\n", header_list, field_names ) 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 %s\nField names: \n %s\n", header_list, field_names ) return False else: return True
[docs] def _delete_top_row_and_compress( 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: next(f_in) for line in f_in: f_out.write(line) return fn_output