def get_api(request, snippet):
from notebook.connectors.hiveserver2 import HS2Api
from notebook.connectors.jdbc import JdbcApi
from notebook.connectors.rdbms import RdbmsApi
from notebook.connectors.pig_batch import PigApi
from notebook.connectors.spark_shell import SparkApi
from notebook.connectors.spark_batch import SparkBatchApi
from notebook.connectors.text import TextApi
interpreter = [interpreter for interpreter in get_interpreters(request.user) if interpreter['type'] == snippet['type']]
if not interpreter:
raise PopupException(_('Snippet type %(type)s is not configured in hue.ini') % snippet)
interpreter = interpreter[0]
interface = interpreter['interface']
if interface == 'hiveserver2':
return HS2Api(user=request.user)
elif interface == 'livy':
return SparkApi(request.user)
elif interface == 'livy-batch':
return SparkBatchApi(request.user)
elif interface == 'text' or interface == 'markdown':
return TextApi(request.user)
elif interface == 'rdbms':
return RdbmsApi(request.user, interpreter=snippet['type'])
elif interface == 'jdbc':
return JdbcApi(request.user, interpreter=interpreter)
elif interface == 'pig':
return PigApi(user=request.user, request=request)
else:
raise PopupException(_('Notebook connector interface not recognized: %s') % interface)
def get_api(user, snippet, fs, jt):
from notebook.connectors.hiveserver2 import HS2Api
from notebook.connectors.jdbc import JdbcApi
from notebook.connectors.mysql import MySqlApi
from notebook.connectors.pig_batch import PigApi
from notebook.connectors.spark_shell import SparkApi
from notebook.connectors.spark_batch import SparkBatchApi
from notebook.connectors.text import TextApi
interpreter = [interpreter for interpreter in get_interpreters() if interpreter['type'] == snippet['type']]
if not interpreter:
raise PopupException(_('Snippet type %(type)s is not configured in hue.ini') % snippet)
interpreter = interpreter[0]
interface = interpreter['interface']
if interface == 'hiveserver2':
return HS2Api(user)
elif interface == 'livy':
return SparkApi(user)
elif interface == 'livy-batch':
return SparkBatchApi(user)
elif interface == 'text':
return TextApi(user)
elif interface == 'mysql':
return MySqlApi(user)
elif interface == 'jdbc':
return JdbcApi(user, interpreter=interpreter)
elif interface == 'pig':
return PigApi(user, fs=fs, jt=jt)
else:
raise PopupException(_('Notebook connector interface not recognized: %s') % interface)
def setUp(self):
self.user = '******'
self.interpreter = {
'name': 'livy',
'options': {
'api_url': 'http://gethue.com:8998'
},
}
self.api = SparkApi(self.user, self.interpreter)
def setUp(self):
self.client = make_logged_in_client(username="******", groupname="default", recreate=True, is_superuser=False)
self.user = User.objects.get(username="******")
self.interpreter = {
'name': 'livy',
'options': {
'api_url': 'http://gethue.com:8998'
},
}
self.api = SparkApi(self.user, self.interpreter)
def get_api(request, snippet):
from notebook.connectors.dataeng import DataEngApi
from notebook.connectors.hiveserver2 import HS2Api
from notebook.connectors.jdbc import JdbcApi
from notebook.connectors.rdbms import RdbmsApi
from notebook.connectors.oozie_batch import OozieApi
from notebook.connectors.solr import SolrApi
from notebook.connectors.spark_shell import SparkApi
from notebook.connectors.spark_batch import SparkBatchApi
from notebook.connectors.text import TextApi
if snippet.get('wasBatchExecuted'):
return OozieApi(user=request.user, request=request)
interpreter = [interpreter for interpreter in get_ordered_interpreters(request.user) if interpreter['type'] == snippet['type']]
if not interpreter:
raise PopupException(_('Snippet type %(type)s is not configured in hue.ini') % snippet)
interpreter = interpreter[0]
interface = interpreter['interface']
# Multi cluster
cluster = Cluster(request.user)
if cluster and cluster.get_type() == 'dataeng':
interface = 'dataeng'
if interface == 'hiveserver2':
return HS2Api(user=request.user, request=request)
elif interface == 'oozie':
return OozieApi(user=request.user, request=request)
elif interface == 'livy':
return SparkApi(request.user)
elif interface == 'livy-batch':
return SparkBatchApi(request.user)
elif interface == 'text' or interface == 'markdown':
return TextApi(request.user)
elif interface == 'rdbms':
return RdbmsApi(request.user, interpreter=snippet['type'])
elif interface == 'dataeng':
return DataEngApi(user=request.user, request=request, cluster_name=cluster.get_interface())
elif interface == 'jdbc':
return JdbcApi(request.user, interpreter=interpreter)
elif interface == 'solr':
return SolrApi(request.user, interpreter=interpreter)
elif interface == 'pig':
return OozieApi(user=request.user, request=request) # Backward compatibility until Hue 4
else:
raise PopupException(_('Notebook connector interface not recognized: %s') % interface)
def get_api(request, snippet):
from notebook.connectors.oozie_batch import OozieApi
if snippet.get('wasBatchExecuted') and not TASK_SERVER.ENABLED.get():
return OozieApi(user=request.user, request=request)
if snippet.get('type') == 'report':
snippet['type'] = 'impala'
patch_snippet_for_connector(snippet)
connector_name = snippet['type']
if has_connectors() and snippet.get('type') == 'hello' and is_admin(
request.user):
interpreter = snippet.get('interpreter')
else:
interpreter = get_interpreter(connector_type=connector_name,
user=request.user)
interface = interpreter['interface']
if get_cluster_config(request.user)['has_computes']:
compute = json.loads(request.POST.get(
'cluster',
'""')) # Via Catalog autocomplete API or Notebook create sessions.
if compute == '""' or compute == 'undefined':
compute = None
if not compute and snippet.get('compute'): # Via notebook.ko.js
interpreter['compute'] = snippet['compute']
LOG.debug('Selected interpreter %s interface=%s compute=%s' %
(interpreter['type'], interface, interpreter.get('compute')
and interpreter['compute']['name']))
if interface == 'hiveserver2' or interface == 'hms':
from notebook.connectors.hiveserver2 import HS2Api
return HS2Api(user=request.user,
request=request,
interpreter=interpreter)
elif interface == 'oozie':
return OozieApi(user=request.user, request=request)
elif interface == 'livy':
from notebook.connectors.spark_shell import SparkApi
return SparkApi(request.user, interpreter=interpreter)
elif interface == 'livy-batch':
from notebook.connectors.spark_batch import SparkBatchApi
return SparkBatchApi(request.user, interpreter=interpreter)
elif interface == 'text' or interface == 'markdown':
from notebook.connectors.text import TextApi
return TextApi(request.user)
elif interface == 'rdbms':
from notebook.connectors.rdbms import RdbmsApi
return RdbmsApi(request.user,
interpreter=snippet['type'],
query_server=snippet.get('query_server'))
elif interface == 'jdbc':
if interpreter['options'] and interpreter['options'].get(
'url', '').find('teradata') >= 0:
from notebook.connectors.jdbc_teradata import JdbcApiTeradata
return JdbcApiTeradata(request.user, interpreter=interpreter)
if interpreter['options'] and interpreter['options'].get(
'url', '').find('awsathena') >= 0:
from notebook.connectors.jdbc_athena import JdbcApiAthena
return JdbcApiAthena(request.user, interpreter=interpreter)
elif interpreter['options'] and interpreter['options'].get(
'url', '').find('presto') >= 0:
from notebook.connectors.jdbc_presto import JdbcApiPresto
return JdbcApiPresto(request.user, interpreter=interpreter)
elif interpreter['options'] and interpreter['options'].get(
'url', '').find('clickhouse') >= 0:
from notebook.connectors.jdbc_clickhouse import JdbcApiClickhouse
return JdbcApiClickhouse(request.user, interpreter=interpreter)
elif interpreter['options'] and interpreter['options'].get(
'url', '').find('vertica') >= 0:
from notebook.connectors.jdbc_vertica import JdbcApiVertica
return JdbcApiVertica(request.user, interpreter=interpreter)
else:
from notebook.connectors.jdbc import JdbcApi
return JdbcApi(request.user, interpreter=interpreter)
elif interface == 'teradata':
from notebook.connectors.jdbc_teradata import JdbcApiTeradata
return JdbcApiTeradata(request.user, interpreter=interpreter)
elif interface == 'athena':
from notebook.connectors.jdbc_athena import JdbcApiAthena
return JdbcApiAthena(request.user, interpreter=interpreter)
elif interface == 'presto':
from notebook.connectors.jdbc_presto import JdbcApiPresto
return JdbcApiPresto(request.user, interpreter=interpreter)
elif interface == 'sqlalchemy':
from notebook.connectors.sql_alchemy import SqlAlchemyApi
return SqlAlchemyApi(request.user, interpreter=interpreter)
elif interface == 'solr':
from notebook.connectors.solr import SolrApi
return SolrApi(request.user, interpreter=interpreter)
elif interface == 'hbase':
from notebook.connectors.hbase import HBaseApi
return HBaseApi(request.user)
elif interface == 'ksql':
from notebook.connectors.ksql import KSqlApi
return KSqlApi(request.user, interpreter=interpreter)
elif interface == 'flink':
from notebook.connectors.flink_sql import FlinkSqlApi
return FlinkSqlApi(request.user, interpreter=interpreter)
elif interface == 'kafka':
from notebook.connectors.kafka import KafkaApi
return KafkaApi(request.user)
elif interface == 'pig':
return OozieApi(user=request.user,
request=request) # Backward compatibility until Hue 4
else:
raise PopupException(
_('Notebook connector interface not recognized: %s') % interface)
def get_api(request, snippet):
from notebook.connectors.oozie_batch import OozieApi
if snippet.get('wasBatchExecuted'):
return OozieApi(user=request.user, request=request)
if snippet['type'] == 'report':
snippet['type'] = 'impala'
interpreter = [
interpreter for interpreter in get_ordered_interpreters(request.user)
if interpreter['type'] == snippet['type']
]
if not interpreter:
if snippet['type'] == 'hbase':
interpreter = [{
'name': 'hbase',
'type': 'hbase',
'interface': 'hbase',
'options': {},
'is_sql': False
}]
elif snippet['type'] == 'kafka':
interpreter = [{
'name': 'kafka',
'type': 'kafka',
'interface': 'kafka',
'options': {},
'is_sql': False
}]
elif snippet['type'] == 'solr':
interpreter = [{
'name': 'solr',
'type': 'solr',
'interface': 'solr',
'options': {},
'is_sql': False
}]
else:
raise PopupException(
_('Snippet type %(type)s is not configured in hue.ini') %
snippet)
interpreter = interpreter[0]
interface = interpreter['interface']
# Multi cluster
cluster = json.loads(request.POST.get('cluster', '""')) # Via Catalog API
if cluster == 'undefined':
cluster = None
if not cluster and snippet.get('compute'): # Via notebook.ko.js
cluster = snippet.get('compute').get('id')
if cluster and 'crn:altus:dataware:' in cluster:
interface = 'altus-adb'
if cluster:
LOG.info('Selected cluster %s' % cluster)
if interface == 'hiveserver2':
from notebook.connectors.hiveserver2 import HS2Api
return HS2Api(user=request.user, request=request, cluster=cluster)
elif interface == 'oozie':
return OozieApi(user=request.user, request=request)
elif interface == 'livy':
from notebook.connectors.spark_shell import SparkApi
return SparkApi(request.user)
elif interface == 'livy-batch':
from notebook.connectors.spark_batch import SparkBatchApi
return SparkBatchApi(request.user)
elif interface == 'text' or interface == 'markdown':
from notebook.connectors.text import TextApi
return TextApi(request.user)
elif interface == 'rdbms':
from notebook.connectors.rdbms import RdbmsApi
return RdbmsApi(request.user, interpreter=snippet['type'])
elif interface == 'altus-adb':
from notebook.connectors.altus_adb import AltusAdbApi
return AltusAdbApi(user=request.user,
cluster_name=cluster,
request=request)
elif interface == 'dataeng':
from notebook.connectors.dataeng import DataEngApi
return DataEngApi(user=request.user,
request=request,
cluster_name=cluster.get('name'))
elif interface == 'jdbc' or interface == 'teradata':
from notebook.connectors.jdbc import JdbcApi
return JdbcApi(request.user, interpreter=interpreter)
elif interface == 'sqlalchemy':
from notebook.connectors.sqlalchemyapi import SqlAlchemyApi
return SqlAlchemyApi(request.user, interpreter=interpreter)
elif interface == 'solr':
from notebook.connectors.solr import SolrApi
return SolrApi(request.user, interpreter=interpreter)
elif interface == 'hbase':
from notebook.connectors.hbase import HBaseApi
return HBaseApi(request.user)
elif interface == 'kafka':
from notebook.connectors.kafka import KafkaApi
return KafkaApi(request.user)
elif interface == 'pig':
return OozieApi(user=request.user,
request=request) # Backward compatibility until Hue 4
else:
raise PopupException(
_('Notebook connector interface not recognized: %s') % interface)
def get_api(request, snippet):
from notebook.connectors.oozie_batch import OozieApi
if snippet.get('wasBatchExecuted'):
return OozieApi(user=request.user, request=request)
if snippet['type'] == 'report':
snippet['type'] = 'impala'
interpreter = [
interpreter for interpreter in get_ordered_interpreters(request.user)
if snippet['type'] in (interpreter['type'], interpreter['interface'])
]
if not interpreter:
if snippet['type'] == 'hbase':
interpreter = [{
'name': 'hbase',
'type': 'hbase',
'interface': 'hbase',
'options': {},
'is_sql': False
}]
elif snippet['type'] == 'kafka':
interpreter = [{
'name': 'kafka',
'type': 'kafka',
'interface': 'kafka',
'options': {},
'is_sql': False
}]
elif snippet['type'] == 'solr':
interpreter = [{
'name': 'solr',
'type': 'solr',
'interface': 'solr',
'options': {},
'is_sql': False
}]
elif snippet['type'] == 'custom':
interpreter = [{
'name': snippet['name'],
'type': snippet['type'],
'interface': snippet['interface'],
'options': snippet.get('options', {}),
'is_sql': False
}]
else:
raise PopupException(
_('Snippet type %(type)s is not configured.') % snippet)
interpreter = interpreter[0]
interface = interpreter['interface']
if CONNECTORS.IS_ENABLED.get():
cluster = {
'connector': snippet['type'],
'id': interpreter['type'],
}
snippet['type'] = snippet['type'].split('-', 2)[0]
cluster.update(interpreter['options'])
# Multi cluster
elif has_multi_cluster():
cluster = json.loads(request.POST.get(
'cluster',
'""')) # Via Catalog autocomplete API or Notebook create sessions
if cluster == '""' or cluster == 'undefined':
cluster = None
if not cluster and snippet.get('compute'): # Via notebook.ko.js
cluster = snippet['compute']
else:
cluster = None
cluster_name = cluster.get('id') if cluster else None
if cluster and 'altus:dataware:k8s' in cluster_name:
interface = 'hiveserver2'
elif cluster and 'crn:altus:dataware:' in cluster_name:
interface = 'altus-adb'
elif cluster and 'crn:altus:dataeng:' in cluster_name:
interface = 'dataeng'
LOG.info('Selected cluster %s %s interface %s' %
(cluster_name, cluster, interface))
snippet['interface'] = interface
if interface.startswith('hiveserver2') or interface == 'hms':
from notebook.connectors.hiveserver2 import HS2Api
return HS2Api(user=request.user,
request=request,
cluster=cluster,
interface=interface)
elif interface == 'oozie':
return OozieApi(user=request.user, request=request)
elif interface == 'livy':
from notebook.connectors.spark_shell import SparkApi
return SparkApi(request.user)
elif interface == 'livy-batch':
from notebook.connectors.spark_batch import SparkBatchApi
return SparkBatchApi(request.user)
elif interface == 'text' or interface == 'markdown':
from notebook.connectors.text import TextApi
return TextApi(request.user)
elif interface == 'rdbms':
from notebook.connectors.rdbms import RdbmsApi
return RdbmsApi(request.user,
interpreter=snippet['type'],
query_server=snippet.get('query_server'))
elif interface == 'altus-adb':
from notebook.connectors.altus_adb import AltusAdbApi
return AltusAdbApi(user=request.user,
cluster_name=cluster_name,
request=request)
elif interface == 'dataeng':
from notebook.connectors.dataeng import DataEngApi
return DataEngApi(user=request.user,
request=request,
cluster_name=cluster_name)
elif interface == 'jdbc':
if interpreter['options'] and interpreter['options'].get(
'url', '').find('teradata') >= 0:
from notebook.connectors.jdbc_teradata import JdbcApiTeradata
return JdbcApiTeradata(request.user, interpreter=interpreter)
if interpreter['options'] and interpreter['options'].get(
'url', '').find('awsathena') >= 0:
from notebook.connectors.jdbc_athena import JdbcApiAthena
return JdbcApiAthena(request.user, interpreter=interpreter)
elif interpreter['options'] and interpreter['options'].get(
'url', '').find('presto') >= 0:
from notebook.connectors.jdbc_presto import JdbcApiPresto
return JdbcApiPresto(request.user, interpreter=interpreter)
elif interpreter['options'] and interpreter['options'].get(
'url', '').find('clickhouse') >= 0:
from notebook.connectors.jdbc_clickhouse import JdbcApiClickhouse
return JdbcApiClickhouse(request.user, interpreter=interpreter)
else:
from notebook.connectors.jdbc import JdbcApi
return JdbcApi(request.user, interpreter=interpreter)
elif interface == 'teradata':
from notebook.connectors.jdbc import JdbcApiTeradata
return JdbcApiTeradata(request.user, interpreter=interpreter)
elif interface == 'athena':
from notebook.connectors.jdbc import JdbcApiAthena
return JdbcApiAthena(request.user, interpreter=interpreter)
elif interface == 'presto':
from notebook.connectors.jdbc_presto import JdbcApiPresto
return JdbcApiPresto(request.user, interpreter=interpreter)
elif interface == 'sqlalchemy':
from notebook.connectors.sqlalchemyapi import SqlAlchemyApi
return SqlAlchemyApi(request.user, interpreter=interpreter)
elif interface == 'solr':
from notebook.connectors.solr import SolrApi
return SolrApi(request.user, interpreter=interpreter)
elif interface == 'hbase':
from notebook.connectors.hbase import HBaseApi
return HBaseApi(request.user)
elif interface == 'kafka':
from notebook.connectors.kafka import KafkaApi
return KafkaApi(request.user)
elif interface == 'pig':
return OozieApi(user=request.user,
request=request) # Backward compatibility until Hue 4
else:
raise PopupException(
_('Notebook connector interface not recognized: %s') % interface)
def setUp(self):
self.user = '******'
self.api = SparkApi(self.user)
