a4c010ba-78be-4818-8e6f-1da08c6af280

Committed 31 Aug 2023 11:59PM UTC coverage: 70.992% (-10.6%) from 81.552%

Build # a4c010ba-78be-4818-8e6f-1da08c6af280

Build Type

push

circle-ci

Committed by

web-flow

Commit Message

Merge branch 'staging' into evadb_staging

Run Details

54 of 54 new or added lines in 3 files covered. (100.0%)

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79.22

/evadb/executor/executor_utils.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.
import glob
import os
from pathlib import Path
from typing import TYPE_CHECKING, Generator, List

if TYPE_CHECKING:
    from evadb.catalog.catalog_manager import CatalogManager

from evadb.catalog.catalog_type import VectorStoreType
from evadb.expression.abstract_expression import AbstractExpression
from evadb.expression.function_expression import FunctionExpression
from evadb.models.storage.batch import Batch
from evadb.parser.table_ref import TableInfo
from evadb.parser.types import FileFormatType
from evadb.readers.document.registry import SUPPORTED_TYPES
from evadb.utils.generic_utils import try_to_import_cv2
from evadb.utils.logging_manager import logger


class ExecutorError(Exception):
    pass


def apply_project(
    batch: Batch, project_list: List[AbstractExpression], catalog: "CatalogManager"
):
    if not batch.empty() and project_list:
        batches = [expr.evaluate(batch) for expr in project_list]
        batch = Batch.merge_column_wise(batches)

        # persist stats of function expression
        for expr in project_list:
            for func_expr in expr.find_all(FunctionExpression):
                if func_expr.udf_obj and func_expr._stats:
                    udf_id = func_expr.udf_obj.row_id
                    catalog.upsert_udf_cost_catalog_entry(
                        udf_id, func_expr.udf_obj.name, func_expr._stats.prev_cost
                    )
    return batch


def apply_predicate(
    batch: Batch, predicate: AbstractExpression, catalog: "CatalogManager"
) -> Batch:
    if not batch.empty() and predicate is not None:
        outcomes = predicate.evaluate(batch)
        batch.drop_zero(outcomes)
        batch.reset_index()

        # persist stats of function expression
        for func_expr in predicate.find_all(FunctionExpression):
            if func_expr.udf_obj and func_expr._stats:
                udf_id = func_expr.udf_obj.row_id
                catalog.upsert_udf_cost_catalog_entry(
                    udf_id, func_expr.udf_obj.name, func_expr._stats.prev_cost
                )
    return batch


def handle_if_not_exists(
    catalog: "CatalogManager", table_info: TableInfo, if_not_exist=False
):
    # Table exists
    if catalog.check_table_exists(
        table_info.table_name,
        table_info.database_name,
    ):
        err_msg = "Table: {} already exists".format(table_info)
        if if_not_exist:
            logger.warn(err_msg)
            return True
        else:
            logger.error(err_msg)
            raise ExecutorError(err_msg)
    # Table does not exist
    else:
        return False


def validate_image(image_path: Path) -> bool:
    try:
        try_to_import_cv2()
        import cv2

        data = cv2.imread(str(image_path))
        return data is not None
    except Exception as e:
        logger.warning(
            f"Unexpected Exception {e} occurred while reading image file {image_path}"
        )
        return False


def iter_path_regex(path_regex: Path) -> Generator[str, None, None]:
    return glob.iglob(os.path.expanduser(path_regex), recursive=True)


def validate_video(video_path: Path) -> bool:
    try:
        try_to_import_cv2()
        import cv2

        vid = cv2.VideoCapture(str(video_path))
        if not vid.isOpened():
            return False
        return True
    except Exception as e:
        logger.warning(
            f"Unexpected Exception {e} occurred while reading video file {video_path}"
        )


def validate_document(doc_path: Path) -> bool:
    return doc_path.suffix in SUPPORTED_TYPES


def validate_pdf(doc_path: Path) -> bool:
    return doc_path.suffix == ".pdf"


def validate_media(file_path: Path, media_type: FileFormatType) -> bool:
    if media_type == FileFormatType.VIDEO:
        return validate_video(file_path)
    elif media_type == FileFormatType.IMAGE:
        return validate_image(file_path)
    elif media_type == FileFormatType.DOCUMENT:
        return validate_document(file_path)
    elif media_type == FileFormatType.PDF:
        return validate_pdf(file_path)
    else:
        raise ValueError(f"Unsupported Media type {str(media_type)}")


def handle_vector_store_params(
    vector_store_type: VectorStoreType, index_path: str
) -> dict:
    """Handle vector store parameters based on the vector store type and index path.

    Args:
        vector_store_type (VectorStoreType): The type of vector store.
        index_path (str): The path to store the index.

    Returns:
        dict: Dictionary containing the appropriate vector store parameters.


    Raises:
        ValueError: If the vector store type in the node is not supported.
    """
    if vector_store_type == VectorStoreType.FAISS:
        return {"index_path": index_path}
    elif vector_store_type == VectorStoreType.QDRANT:
        return {"index_db": str(Path(index_path).parent)}
    else:
        raise ValueError("Unsupported vector store type: {}".format(vector_store_type))

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	import glob	1✔
16	import os	1✔
17	from pathlib import Path	1✔
18	from typing import TYPE_CHECKING, Generator, List	1✔
19
20	if TYPE_CHECKING:
21	from evadb.catalog.catalog_manager import CatalogManager
22
23	from evadb.catalog.catalog_type import VectorStoreType	1✔
24	from evadb.expression.abstract_expression import AbstractExpression	1✔
25	from evadb.expression.function_expression import FunctionExpression	1✔
26	from evadb.models.storage.batch import Batch	1✔
27	from evadb.parser.table_ref import TableInfo	1✔
28	from evadb.parser.types import FileFormatType	1✔
29	from evadb.readers.document.registry import SUPPORTED_TYPES	1✔
30	from evadb.utils.generic_utils import try_to_import_cv2	1✔
31	from evadb.utils.logging_manager import logger	1✔
32
33
34	class ExecutorError(Exception):	1✔
35	pass	1✔
36
37
38	def apply_project(	1✔
39	batch: Batch, project_list: List[AbstractExpression], catalog: "CatalogManager"
40	):
41	if not batch.empty() and project_list:	1✔
42	batches = [expr.evaluate(batch) for expr in project_list]	1✔
43	batch = Batch.merge_column_wise(batches)	1✔
44
45	# persist stats of function expression
46	for expr in project_list:	1✔
47	for func_expr in expr.find_all(FunctionExpression):	1✔
48	if func_expr.udf_obj and func_expr._stats:	×
49	udf_id = func_expr.udf_obj.row_id	×
50	catalog.upsert_udf_cost_catalog_entry(	×
51	udf_id, func_expr.udf_obj.name, func_expr._stats.prev_cost
52	)
53	return batch	1✔
54
55
56	def apply_predicate(	1✔
57	batch: Batch, predicate: AbstractExpression, catalog: "CatalogManager"
58	) -> Batch:
59	if not batch.empty() and predicate is not None:	1✔
60	outcomes = predicate.evaluate(batch)	1✔
61	batch.drop_zero(outcomes)	1✔
62	batch.reset_index()	1✔
63
64	# persist stats of function expression
65	for func_expr in predicate.find_all(FunctionExpression):	1✔
66	if func_expr.udf_obj and func_expr._stats:	×
67	udf_id = func_expr.udf_obj.row_id	×
68	catalog.upsert_udf_cost_catalog_entry(	×
69	udf_id, func_expr.udf_obj.name, func_expr._stats.prev_cost
70	)
71	return batch	1✔
72
73
74	def handle_if_not_exists(	1✔
75	catalog: "CatalogManager", table_info: TableInfo, if_not_exist=False
76	):
77	# Table exists
78	if catalog.check_table_exists(	1✔
79	table_info.table_name,
80	table_info.database_name,
81	):
82	err_msg = "Table: {} already exists".format(table_info)	×
83	if if_not_exist:	×
84	logger.warn(err_msg)	×
85	return True	×
86	else:
87	logger.error(err_msg)	×
88	raise ExecutorError(err_msg)
89	# Table does not exist
90	else:
91	return False	1✔
92
93
94	def validate_image(image_path: Path) -> bool:	1✔
95	try:	1✔
96	try_to_import_cv2()	1✔
97	import cv2	1✔
98
99	data = cv2.imread(str(image_path))	1✔
100	return data is not None	1✔
101	except Exception as e:
102	logger.warning(
103	f"Unexpected Exception {e} occurred while reading image file {image_path}"
104	)
105	return False
106
107
108	def iter_path_regex(path_regex: Path) -> Generator[str, None, None]:	1✔
109	return glob.iglob(os.path.expanduser(path_regex), recursive=True)	1✔
110
111
112	def validate_video(video_path: Path) -> bool:	1✔
113	try:	1✔
114	try_to_import_cv2()	1✔
115	import cv2	1✔
116
117	vid = cv2.VideoCapture(str(video_path))	1✔
118	if not vid.isOpened():	1✔
119	return False	×
120	return True	1✔
121	except Exception as e:
122	logger.warning(
123	f"Unexpected Exception {e} occurred while reading video file {video_path}"
124	)
125
126
127	def validate_document(doc_path: Path) -> bool:	1✔
128	return doc_path.suffix in SUPPORTED_TYPES	×
129
130
131	def validate_pdf(doc_path: Path) -> bool:	1✔
132	return doc_path.suffix == ".pdf"	1✔
133
134
135	def validate_media(file_path: Path, media_type: FileFormatType) -> bool:	1✔
136	if media_type == FileFormatType.VIDEO:	1✔
137	return validate_video(file_path)	1✔
138	elif media_type == FileFormatType.IMAGE:	1✔
139	return validate_image(file_path)	1✔
140	elif media_type == FileFormatType.DOCUMENT:	1✔
141	return validate_document(file_path)	×
142	elif media_type == FileFormatType.PDF:	1✔
143	return validate_pdf(file_path)	1✔
144	else:
145	raise ValueError(f"Unsupported Media type {str(media_type)}")
146
147
148	def handle_vector_store_params(	1✔
149	vector_store_type: VectorStoreType, index_path: str
150	) -> dict:
151	"""Handle vector store parameters based on the vector store type and index path.
152
153	Args:
154	vector_store_type (VectorStoreType): The type of vector store.
155	index_path (str): The path to store the index.
156
157	Returns:
158	dict: Dictionary containing the appropriate vector store parameters.
159
160
161	Raises:
162	ValueError: If the vector store type in the node is not supported.
163	"""
164	if vector_store_type == VectorStoreType.FAISS:	1✔
165	return {"index_path": index_path}	1✔
166	elif vector_store_type == VectorStoreType.QDRANT:	×
167	return {"index_db": str(Path(index_path).parent)}	×
168	else:
169	raise ValueError("Unsupported vector store type: {}".format(vector_store_type))

georgia-tech-db / eva / a4c010ba-78be-4818-8e6f-1da08c6af280

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