Source code for airflow.contrib.operators.cassandra_to_gcs

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from __future__ import unicode_literals

import json
from builtins import str
from base64 import b64encode
from cassandra.util import Date, Time, SortedSet, OrderedMapSerializedKey
from datetime import datetime
from decimal import Decimal
from six import text_type, binary_type, PY3
from tempfile import NamedTemporaryFile
from uuid import UUID

from airflow.contrib.hooks.gcs_hook import GoogleCloudStorageHook
from airflow.contrib.hooks.cassandra_hook import CassandraHook
from airflow.exceptions import AirflowException
from airflow.models import BaseOperator
from airflow.utils.decorators import apply_defaults

[docs]class CassandraToGoogleCloudStorageOperator(BaseOperator): """ Copy data from Cassandra to Google cloud storage in JSON format Note: Arrays of arrays are not supported. """ template_fields = ('cql', 'bucket', 'filename', 'schema_filename',) template_ext = ('.cql',) ui_color = '#a0e08c' @apply_defaults def __init__(self, cql, bucket, filename, schema_filename=None, approx_max_file_size_bytes=1900000000, cassandra_conn_id='cassandra_default', google_cloud_storage_conn_id='google_cloud_default', delegate_to=None, *args, **kwargs): """ :param cql: The CQL to execute on the Cassandra table. :type cql: string :param bucket: The bucket to upload to. :type bucket: string :param filename: The filename to use as the object name when uploading to Google cloud storage. A {} should be specified in the filename to allow the operator to inject file numbers in cases where the file is split due to size. :type filename: string :param schema_filename: If set, the filename to use as the object name when uploading a .json file containing the BigQuery schema fields for the table that was dumped from MySQL. :type schema_filename: string :param approx_max_file_size_bytes: This operator supports the ability to split large table dumps into multiple files (see notes in the filenamed param docs above). Google cloud storage allows for files to be a maximum of 4GB. This param allows developers to specify the file size of the splits. :type approx_max_file_size_bytes: long :param cassandra_conn_id: Reference to a specific Cassandra hook. :type cassandra_conn_id: string :param google_cloud_storage_conn_id: Reference to a specific Google cloud storage hook. :type google_cloud_storage_conn_id: string :param delegate_to: The account to impersonate, if any. For this to work, the service account making the request must have domain-wide delegation enabled. :type delegate_to: string """ super(CassandraToGoogleCloudStorageOperator, self).__init__(*args, **kwargs) self.cql = cql self.bucket = bucket self.filename = filename self.schema_filename = schema_filename self.approx_max_file_size_bytes = approx_max_file_size_bytes self.cassandra_conn_id = cassandra_conn_id self.google_cloud_storage_conn_id = google_cloud_storage_conn_id self.delegate_to = delegate_to self.hook = None # Default Cassandra to BigQuery type mapping CQL_TYPE_MAP = { 'BytesType': 'BYTES', 'DecimalType': 'FLOAT', 'UUIDType': 'BYTES', 'BooleanType': 'BOOL', 'ByteType': 'INTEGER', 'AsciiType': 'STRING', 'FloatType': 'FLOAT', 'DoubleType': 'FLOAT', 'LongType': 'INTEGER', 'Int32Type': 'INTEGER', 'IntegerType': 'INTEGER', 'InetAddressType': 'STRING', 'CounterColumnType': 'INTEGER', 'DateType': 'TIMESTAMP', 'SimpleDateType': 'DATE', 'TimestampType': 'TIMESTAMP', 'TimeUUIDType': 'BYTES', 'ShortType': 'INTEGER', 'TimeType': 'TIME', 'DurationType': 'INTEGER', 'UTF8Type': 'STRING', 'VarcharType': 'STRING', } def execute(self, context): cursor = self._query_cassandra() files_to_upload = self._write_local_data_files(cursor) # If a schema is set, create a BQ schema JSON file. if self.schema_filename: files_to_upload.update(self._write_local_schema_file(cursor)) # Flush all files before uploading for file_handle in files_to_upload.values(): file_handle.flush() self._upload_to_gcs(files_to_upload) # Close all temp file handles. for file_handle in files_to_upload.values(): file_handle.close() # Close all sessions and connection associated with this Cassandra cluster self.hook.shutdown_cluster() def _query_cassandra(self): """ Queries cassandra and returns a cursor to the results. """ self.hook = CassandraHook(cassandra_conn_id=self.cassandra_conn_id) session = self.hook.get_conn() cursor = session.execute(self.cql) return cursor def _write_local_data_files(self, cursor): """ Takes a cursor, and writes results to a local file. :return: A dictionary where keys are filenames to be used as object names in GCS, and values are file handles to local files that contain the data for the GCS objects. """ file_no = 0 tmp_file_handle = NamedTemporaryFile(delete=True) tmp_file_handles = {self.filename.format(file_no): tmp_file_handle} for row in cursor: row_dict = self.generate_data_dict(row._fields, row) s = json.dumps(row_dict) if PY3: s = s.encode('utf-8') tmp_file_handle.write(s) # Append newline to make dumps BigQuery compatible. tmp_file_handle.write(b'\n') if tmp_file_handle.tell() >= self.approx_max_file_size_bytes: file_no += 1 tmp_file_handle = NamedTemporaryFile(delete=True) tmp_file_handles[self.filename.format(file_no)] = tmp_file_handle return tmp_file_handles def _write_local_schema_file(self, cursor): """ Takes a cursor, and writes the BigQuery schema for the results to a local file system. :return: A dictionary where key is a filename to be used as an object name in GCS, and values are file handles to local files that contains the BigQuery schema fields in .json format. """ schema = [] tmp_schema_file_handle = NamedTemporaryFile(delete=True) for name, type in zip(cursor.column_names, cursor.column_types): schema.append(self.generate_schema_dict(name, type)) json_serialized_schema = json.dumps(schema) if PY3: json_serialized_schema = json_serialized_schema.encode('utf-8') tmp_schema_file_handle.write(json_serialized_schema) return {self.schema_filename: tmp_schema_file_handle} def _upload_to_gcs(self, files_to_upload): hook = GoogleCloudStorageHook( google_cloud_storage_conn_id=self.google_cloud_storage_conn_id, delegate_to=self.delegate_to) for object, tmp_file_handle in files_to_upload.items(): hook.upload(self.bucket, object,, 'application/json') @classmethod def generate_data_dict(cls, names, values): row_dict = {} for name, value in zip(names, values): row_dict.update({name: cls.convert_value(name, value)}) return row_dict @classmethod def convert_value(cls, name, value): if not value: return value elif isinstance(value, (text_type, int, float, bool, dict)): return value elif isinstance(value, binary_type): return b64encode(value).decode('ascii') elif isinstance(value, UUID): return b64encode(value.bytes).decode('ascii') elif isinstance(value, (datetime, Date)): return str(value) elif isinstance(value, Decimal): return float(value) elif isinstance(value, Time): return str(value).split('.')[0] elif isinstance(value, (list, SortedSet)): return cls.convert_array_types(name, value) elif hasattr(value, '_fields'): return cls.convert_user_type(name, value) elif isinstance(value, tuple): return cls.convert_tuple_type(name, value) elif isinstance(value, OrderedMapSerializedKey): return cls.convert_map_type(name, value) else: raise AirflowException('unexpected value: ' + str(value)) @classmethod def convert_array_types(cls, name, value): return [cls.convert_value(name, nested_value) for nested_value in value]
[docs] @classmethod def convert_user_type(cls, name, value): """ Converts a user type to RECORD that contains n fields, where n is the number of attributes. Each element in the user type class will be converted to its corresponding data type in BQ. """ names = value._fields values = [cls.convert_value(name, getattr(value, name)) for name in names] return cls.generate_data_dict(names, values)
[docs] @classmethod def convert_tuple_type(cls, name, value): """ Converts a tuple to RECORD that contains n fields, each will be converted to its corresponding data type in bq and will be named 'field_<index>', where index is determined by the order of the tuple elments defined in cassandra. """ names = ['field_' + str(i) for i in range(len(value))] values = [cls.convert_value(name, value) for name, value in zip(names, value)] return cls.generate_data_dict(names, values)
[docs] @classmethod def convert_map_type(cls, name, value): """ Converts a map to a repeated RECORD that contains two fields: 'key' and 'value', each will be converted to its corresopnding data type in BQ. """ converted_map = [] for k, v in zip(value.keys(), value.values()): converted_map.append({ 'key': cls.convert_value('key', k), 'value': cls.convert_value('value', v) }) return converted_map
@classmethod def generate_schema_dict(cls, name, type): field_schema = dict() field_schema.update({'name': name}) field_schema.update({'type': cls.get_bq_type(type)}) field_schema.update({'mode': cls.get_bq_mode(type)}) fields = cls.get_bq_fields(name, type) if fields: field_schema.update({'fields': fields}) return field_schema @classmethod def get_bq_fields(cls, name, type): fields = [] if not cls.is_simple_type(type): names, types = [], [] if cls.is_array_type(type) and cls.is_record_type(type.subtypes[0]): names = type.subtypes[0].fieldnames types = type.subtypes[0].subtypes elif cls.is_record_type(type): names = type.fieldnames types = type.subtypes if types and not names and type.cassname == 'TupleType': names = ['field_' + str(i) for i in range(len(types))] elif types and not names and type.cassname == 'MapType': names = ['key', 'value'] for name, type in zip(names, types): field = cls.generate_schema_dict(name, type) fields.append(field) return fields @classmethod def is_simple_type(cls, type): return type.cassname in CassandraToGoogleCloudStorageOperator.CQL_TYPE_MAP @classmethod def is_array_type(cls, type): return type.cassname in ['ListType', 'SetType'] @classmethod def is_record_type(cls, type): return type.cassname in ['UserType', 'TupleType', 'MapType'] @classmethod def get_bq_type(cls, type): if cls.is_simple_type(type): return CassandraToGoogleCloudStorageOperator.CQL_TYPE_MAP[type.cassname] elif cls.is_record_type(type): return 'RECORD' elif cls.is_array_type(type): return cls.get_bq_type(type.subtypes[0]) else: raise AirflowException('Not a supported type: ' + type.cassname) @classmethod def get_bq_mode(cls, type): if cls.is_array_type(type) or type.cassname == 'MapType': return 'REPEATED' elif cls.is_record_type(type) or cls.is_simple_type(type): return 'NULLABLE' else: raise AirflowException('Not a supported type: ' + type.cassname)