def test_guess_format_invalid_csv_format(self):
indexer = Indexer("test", None)
stream = StringIO.StringIO(IndexerTest.simpleCSVString)
guessed_format = indexer.guess_format({'file': {"stream": stream, "name": "test.csv"}})
guessed_format["fieldSeparator"] = "invalid separator"
fields = indexer.guess_field_types({"file": {"stream": stream, "name": "test.csv"}, "format": guessed_format})['columns']
assert_equal(fields, [])
stream.seek(0)
guessed_format = indexer.guess_format({'file': {"stream": stream, "name": "test.csv"}})
guessed_format["recordSeparator"] = "invalid separator"
fields = indexer.guess_field_types({"file": {"stream": stream, "name": "test.csv"}, "format": guessed_format})['columns']
assert_equal(fields, [])
stream.seek(0)
guessed_format = indexer.guess_format({'file': {"stream": stream, "name": "test.csv"}})
guessed_format["quoteChar"] = "invalid quoteChar"
fields = indexer.guess_field_types({"file": {"stream": stream, "name": "test.csv"}, "format": guessed_format})['columns']
assert_equal(fields, [])
def test_guess_format_invalid_csv_format(self):
indexer = Indexer("test", None)
stream = StringIO.StringIO(IndexerTest.simpleCSVString)
guessed_format = indexer.guess_format(
{'file': {
"stream": stream,
"name": "test.csv"
}})
guessed_format["fieldSeparator"] = "invalid separator"
fields = indexer.guess_field_types({
"file": {
"stream": stream,
"name": "test.csv"
},
"format": guessed_format
})['columns']
assert_equal(fields, [])
stream.seek(0)
guessed_format = indexer.guess_format(
{'file': {
"stream": stream,
"name": "test.csv"
}})
guessed_format["recordSeparator"] = "invalid separator"
fields = indexer.guess_field_types({
"file": {
"stream": stream,
"name": "test.csv"
},
"format": guessed_format
})['columns']
assert_equal(fields, [])
stream.seek(0)
guessed_format = indexer.guess_format(
{'file': {
"stream": stream,
"name": "test.csv"
}})
guessed_format["quoteChar"] = "invalid quoteChar"
fields = indexer.guess_field_types({
"file": {
"stream": stream,
"name": "test.csv"
},
"format": guessed_format
})['columns']
assert_equal(fields, [])
def guess_format(request):
file_format = json.loads(request.POST.get('fileFormat', '{}'))
if file_format['inputFormat'] == 'file':
indexer = Indexer(request.user, request.fs)
stream = request.fs.open(file_format["path"])
format_ = indexer.guess_format({
"file":{
"stream": stream,
"name": file_format['path']
}
})
_convert_format(format_)
elif file_format['inputFormat'] == 'table':
db = dbms.get(request.user)
table_metadata = db.get_table(database=file_format['databaseName'], table_name=file_format['tableName'])
storage = dict([(delim['data_type'], delim['comment']) for delim in table_metadata.storage_details])
if table_metadata.details['properties']['format'] == 'text':
format_ = {"quoteChar": "\"", "recordSeparator": '\\n', "type": "csv", "hasHeader": False, "fieldSeparator": storage['serialization.format']}
elif table_metadata.details['properties']['format'] == 'parquet':
format_ = {"type": "parquet", "hasHeader": False,}
else:
raise PopupException('Hive table format %s is not supported.' % table_metadata.details['properties']['format'])
elif file_format['inputFormat'] == 'query':
format_ = {"quoteChar": "\"", "recordSeparator": "\\n", "type": "csv", "hasHeader": False, "fieldSeparator": "\t"} # \t --> CTRL+A
return JsonResponse(format_)
def guess_format(request):
file_format = json.loads(request.POST.get('fileFormat', '{}'))
if file_format['inputFormat'] == 'file':
indexer = Indexer(request.user, request.fs)
if not request.fs.isfile(file_format["path"]):
raise PopupException(_('Path %(path)s is not a file') % file_format)
stream = request.fs.open(file_format["path"])
format_ = indexer.guess_format({
"file": {
"stream": stream,
"name": file_format['path']
}
})
_convert_format(format_)
elif file_format['inputFormat'] == 'table':
db = dbms.get(request.user)
table_metadata = db.get_table(database=file_format['databaseName'], table_name=file_format['tableName'])
storage = dict([(delim['data_type'], delim['comment']) for delim in table_metadata.storage_details])
if table_metadata.details['properties']['format'] == 'text':
format_ = {"quoteChar": "\"", "recordSeparator": '\\n', "type": "csv", "hasHeader": False, "fieldSeparator": storage['serialization.format']}
elif table_metadata.details['properties']['format'] == 'parquet':
format_ = {"type": "parquet", "hasHeader": False,}
else:
raise PopupException('Hive table format %s is not supported.' % table_metadata.details['properties']['format'])
elif file_format['inputFormat'] == 'query':
format_ = {"quoteChar": "\"", "recordSeparator": "\\n", "type": "csv", "hasHeader": False, "fieldSeparator": "\u0001"}
format_['status'] = 0
return JsonResponse(format_)
def test_guess_csv_format(self):
stream = StringIO.StringIO(IndexerTest.simpleCSVString)
indexer = Indexer("test", None)
guessed_format = indexer.guess_format(
{'file': {
"stream": stream,
"name": "test.csv"
}})
fields = indexer.guess_field_types({
"file": {
"stream": stream,
"name": "test.csv"
},
"format": guessed_format
})['columns']
# test format
expected_format = self.simpleCSVFormat
assert_equal(expected_format, guessed_format)
# test fields
expected_fields = self.simpleCSVFields
for expected, actual in zip(expected_fields, fields):
for key in ("name", "type"):
assert_equal(expected[key], actual[key])
def guess_format(request):
file_format = json.loads(request.POST.get('fileFormat', '{}'))
indexer = Indexer(request.user, request.fs)
stream = request.fs.open(file_format["path"])
format_ = indexer.guess_format({"file":stream})
_convert_format(format_)
return JsonResponse(format_)
def test_end_to_end(self):
if not is_live_cluster():
raise SkipTest()
cluster = shared_cluster()
fs = cluster.fs
collection_name = "test_collection"
indexer = Indexer("test", fs=fs, jt=cluster.jt)
input_loc = "/tmp/test.csv"
# upload the test file to hdfs
fs.create(input_loc, data=TestIndexer.simpleCSVString, overwrite=True)
# open a filestream for the file on hdfs
stream = fs.open(input_loc)
# guess the format of the file
file_type_format = indexer.guess_format(
{'file': {
"stream": stream,
"name": "test.csv"
}})
field_types = indexer.guess_field_types({
"file": {
"stream": stream,
"name": "test.csv"
},
"format": file_type_format
})
format_ = field_types.copy()
format_['format'] = file_type_format
# find a field name available to use for the record's uuid
unique_field = indexer.get_unique_field(format_)
is_unique_generated = indexer.is_unique_generated(format_)
# generate morphline
morphline = indexer.generate_morphline_config(collection_name, format_,
unique_field)
schema_fields = indexer.get_kept_field_list(format_['columns'])
if is_unique_generated:
schema_fields += [{"name": unique_field, "type": "string"}]
# create the collection from the specified fields
collection_manager = CollectionManagerController("test")
if collection_manager.collection_exists(collection_name):
collection_manager.delete_collection(collection_name, None)
collection_manager.create_collection(collection_name,
schema_fields,
unique_key_field=unique_field)
# index the file
indexer.run_morphline(collection_name, morphline, input_loc)
def guess_format(request):
file_format = json.loads(request.POST.get('fileFormat', '{}'))
indexer = Indexer(request.user, request.fs)
stream = request.fs.open(file_format["path"])
format_ = indexer.guess_format(
{"file": {
"stream": stream,
"name": file_format['path']
}})
_convert_format(format_)
return JsonResponse(format_)
def test_end_to_end(self):
if not is_live_cluster() or True: # Skipping as requires morplines libs to be setup
raise SkipTest()
cluster = shared_cluster()
fs = cluster.fs
make_logged_in_client(username="******", groupname="default", recreate=True, is_superuser=False)
user = User.objects.get(username="******")
collection_name = "test_collection"
indexer = Indexer("test", fs=fs, jt=cluster.jt)
input_loc = "/tmp/test.csv"
# upload the test file to hdfs
fs.create(input_loc, data=TestIndexer.simpleCSVString, overwrite=True)
# open a filestream for the file on hdfs
stream = fs.open(input_loc)
# guess the format of the file
file_type_format = indexer.guess_format({'file': {"stream": stream, "name": "test.csv"}})
field_types = indexer.guess_field_types({"file":{"stream": stream, "name": "test.csv"}, "format": file_type_format})
format_ = field_types.copy()
format_['format'] = file_type_format
# find a field name available to use for the record's uuid
unique_field = indexer.get_unique_field(format_)
is_unique_generated = indexer.is_unique_generated(format_)
# generate morphline
morphline = indexer.generate_morphline_config(collection_name, format_, unique_field)
schema_fields = indexer.get_kept_field_list(format_['columns'])
if is_unique_generated:
schema_fields += [{"name": unique_field, "type": "string"}]
# create the collection from the specified fields
collection_manager = CollectionManagerController("test")
if collection_manager.collection_exists(collection_name):
collection_manager.delete_collection(collection_name, None)
collection_manager.create_collection(collection_name, schema_fields, unique_key_field=unique_field)
# index the file
indexer.run_morphline(MockedRequest(user=user, fs=cluster.fs, jt=cluster.jt), collection_name, morphline, input_loc)
def test_guess_csv_format(self):
stream = StringIO.StringIO(TestIndexer.simpleCSVString)
indexer = Indexer("test")
guessed_format = indexer.guess_format({'file': {"stream": stream, "name": "test.csv"}})
fields = indexer.guess_field_types({"file":{"stream": stream, "name": "test.csv"}, "format": guessed_format})['columns']
# test format
expected_format = self.simpleCSVFormat
assert_equal(expected_format, guessed_format)
# test fields
expected_fields = self.simpleCSVFields
for expected, actual in zip(expected_fields, fields):
for key in ("name", "type"):
assert_equal(expected[key], actual[key])
def test_guess_format(self):
stream = StringIO.StringIO(IndexerTest.simpleCSVString)
indexer = Indexer("test", None)
guessed_format = indexer.guess_format({'file': {"stream": stream, "name": "test.csv"}})
fields = indexer.guess_field_types({"file":{"stream": stream, "name": "test.csv"}, "format": guessed_format})['columns']
# test format
assert_equal('csv', guessed_format['type'])
assert_equal(',', guessed_format['fieldSeparator'])
assert_equal('\n', guessed_format['recordSeparator'])
# test fields
expected_fields = [
{
"name": "id",
"type": "long"
},
{
"name": "Rating",
"type": "long"
},
{
"name": "Location",
"type": "string"
},
{
"name": "Name",
"type": "string"
},
{
"name": "Time",
"type": "string"
}
]
for expected, actual in zip(expected_fields, fields):
for key in ("name", "type"):
assert_equal(expected[key], actual[key])
def test_end_to_end(self):
fs = cluster.get_hdfs()
collection_name = "test_collection"
indexer = Indexer("test", fs)
input_loc = "/tmp/test.csv"
# upload the test file to hdfs
fs.create(input_loc, data=IndexerTest.simpleCSVString, overwrite=True)
# open a filestream for the file on hdfs
stream = fs.open(input_loc)
# guess the format of the file
file_type_format = indexer.guess_format({'file': {"stream": stream, "name": "test.csv"}})
field_types = indexer.guess_field_types({"file":{"stream": stream, "name": "test.csv"}, "format": file_type_format})
format_ = field_types.copy()
format_['format'] = file_type_format
# find a field name available to use for the record's uuid
unique_field = indexer.get_uuid_name(format_)
# generate morphline
morphline = indexer.generate_morphline_config(collection_name, format_, unique_field)
schema_fields = [{"name": unique_field, "type": "string"}] + indexer.get_kept_field_list(format_['columns'])
# create the collection from the specified fields
collection_manager = CollectionManagerController("test")
if collection_manager.collection_exists(collection_name):
collection_manager.delete_collection(collection_name, None)
collection_manager.create_collection(collection_name, schema_fields, unique_key_field=unique_field)
# index the file
indexer.run_morphline(collection_name, morphline, input_loc)