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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')
@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)
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)
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:
self.log.info(
"Dumping S3 key %s contents to local file %s", s3_key_object.key, f.name
)
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:
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)
[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
@staticmethod
[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:
f_in.seek(0)
next(f_in)
for line in f_in:
f_out.write(line)
return fn_output