79000c30-425a-4d3d-b9ba-c40b73e104fd

Committed 18 Sep 2023 07:30PM UTC coverage: 79.745% (-0.4%) from 80.158%

Build # 79000c30-425a-4d3d-b9ba-c40b73e104fd

Build Type

push

circle-ci

Committed by

web-flow

Commit Message

Merge branch 'georgia-tech-db:staging' into vector_pinecone

Run Details

164 of 164 new or added lines in 17 files covered. (100.0%)

9563 of 11992 relevant lines covered (79.74%)

1.44 hits per line

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88.89

/evadb/executor/storage_executor.py

# coding=utf-8
# Copyright 2018-2023 EvaDB
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from typing import Iterator

from evadb.catalog.catalog_type import TableType
from evadb.database import EvaDBDatabase
from evadb.executor.abstract_executor import AbstractExecutor
from evadb.executor.executor_utils import ExecutorError
from evadb.models.storage.batch import Batch
from evadb.plan_nodes.storage_plan import StoragePlan
from evadb.storage.storage_engine import StorageEngine
from evadb.utils.logging_manager import logger


class StorageExecutor(AbstractExecutor):
    def __init__(self, db: EvaDBDatabase, node: StoragePlan):
        super().__init__(db, node)

    def exec(self, *args, **kwargs) -> Iterator[Batch]:
        try:
            storage_engine = StorageEngine.factory(self.db, self.node.table)

            if self.node.table.table_type == TableType.VIDEO_DATA:
                return storage_engine.read(
                    self.node.table,
                    self.node.batch_mem_size,
                    predicate=self.node.predicate,
                    sampling_rate=self.node.sampling_rate,
                    sampling_type=self.node.sampling_type,
                    read_audio=self.node.table_ref.get_audio,
                    read_video=self.node.table_ref.get_video,
                )
            elif self.node.table.table_type == TableType.IMAGE_DATA:
                return storage_engine.read(self.node.table)
            elif self.node.table.table_type == TableType.DOCUMENT_DATA:
                return storage_engine.read(self.node.table, self.node.chunk_params)
            elif self.node.table.table_type == TableType.STRUCTURED_DATA:
                return storage_engine.read(self.node.table, self.node.batch_mem_size)
            elif self.node.table.table_type == TableType.NATIVE_DATA:
                return storage_engine.read(self.node.table)
            elif self.node.table.table_type == TableType.PDF_DATA:
                return storage_engine.read(self.node.table)
            else:
                raise ExecutorError(
                    f"Unsupported TableType {self.node.table.table_type} encountered"
                )
        except Exception as e:
            logger.error(e)
            raise ExecutorError(e)

1	# coding=utf-8
2	# Copyright 2018-2023 EvaDB
3	#
4	# Licensed under the Apache License, Version 2.0 (the "License");
5	# you may not use this file except in compliance with the License.
6	# You may obtain a copy of the License at
7	#
8	# http://www.apache.org/licenses/LICENSE-2.0
9	#
10	# Unless required by applicable law or agreed to in writing, software
11	# distributed under the License is distributed on an "AS IS" BASIS,
12	# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
13	# See the License for the specific language governing permissions and
14	# limitations under the License.
15	from typing import Iterator	2✔
16
17	from evadb.catalog.catalog_type import TableType	2✔
18	from evadb.database import EvaDBDatabase	2✔
19	from evadb.executor.abstract_executor import AbstractExecutor	2✔
20	from evadb.executor.executor_utils import ExecutorError	2✔
21	from evadb.models.storage.batch import Batch	2✔
22	from evadb.plan_nodes.storage_plan import StoragePlan	2✔
23	from evadb.storage.storage_engine import StorageEngine	2✔
24	from evadb.utils.logging_manager import logger	2✔
25
26
27	class StorageExecutor(AbstractExecutor):	2✔
28	def __init__(self, db: EvaDBDatabase, node: StoragePlan):	2✔
29	super().__init__(db, node)	2✔
30
31	def exec(self, args, *kwargs) -> Iterator[Batch]:	2✔
32	try:	2✔
33	storage_engine = StorageEngine.factory(self.db, self.node.table)	2✔
34
35	if self.node.table.table_type == TableType.VIDEO_DATA:	2✔
36	return storage_engine.read(	2✔
37	self.node.table,
38	self.node.batch_mem_size,
39	predicate=self.node.predicate,
40	sampling_rate=self.node.sampling_rate,
41	sampling_type=self.node.sampling_type,
42	read_audio=self.node.table_ref.get_audio,
43	read_video=self.node.table_ref.get_video,
44	)
45	elif self.node.table.table_type == TableType.IMAGE_DATA:	2✔
46	return storage_engine.read(self.node.table)	×
47	elif self.node.table.table_type == TableType.DOCUMENT_DATA:	2✔
48	return storage_engine.read(self.node.table, self.node.chunk_params)	×
49	elif self.node.table.table_type == TableType.STRUCTURED_DATA:	2✔
50	return storage_engine.read(self.node.table, self.node.batch_mem_size)	2✔
51	elif self.node.table.table_type == TableType.NATIVE_DATA:	1✔
52	return storage_engine.read(self.node.table)	×
53	elif self.node.table.table_type == TableType.PDF_DATA:	1✔
54	return storage_engine.read(self.node.table)	1✔
55	else:
56	raise ExecutorError(
57	f"Unsupported TableType {self.node.table.table_type} encountered"
58	)
59	except Exception as e:
60	logger.error(e)
61	raise ExecutorError(e)

georgia-tech-db / eva / 79000c30-425a-4d3d-b9ba-c40b73e104fd

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