fix: motif_mining query (#913)

This PR deprecates CREATE MATERIALIZE VIEW query from motif planning
notebook

evadb/optimizer/rules/rules.py

@@ -39,6 +39,7 @@
 from evadb.optimizer.rules.rules_base import Promise, Rule, RuleType
 from evadb.parser.types import JoinType, ParserOrderBySortType
 from evadb.plan_nodes.apply_and_merge_plan import ApplyAndMergePlan
+from evadb.plan_nodes.create_from_select_plan import CreateFromSelectPlan
 from evadb.plan_nodes.exchange_plan import ExchangePlan
 from evadb.plan_nodes.explain_plan import ExplainPlan
 from evadb.plan_nodes.hash_join_build_plan import HashJoinBuildPlan
@@ -716,7 +717,9 @@ def check(self, before: Operator, context: OptimizerContext):
         return True
 
     def apply(self, before: LogicalCreate, context: OptimizerContext):
-        after = CreatePlan(before.video, before.column_list, before.if_not_exists)
+        after = CreateFromSelectPlan(
+            before.video, before.column_list, before.if_not_exists
+        )
         for child in before.children:
             after.append_child(child)
         yield after

evadb/plan_nodes/create_from_select_plan.py

@@ -0,0 +1,71 @@
+# 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 List
+
+from evadb.parser.create_statement import ColumnDefinition
+from evadb.parser.table_ref import TableInfo
+from evadb.plan_nodes.abstract_plan import AbstractPlan
+from evadb.plan_nodes.types import PlanOprType
+
+
+class CreateFromSelectPlan(AbstractPlan):
+    """
+    This plan is used for storing information required for creating
+    a table from select query.
+    Arguments:
+        table_info {TableInfo} -- table info for view to be created in storage
+        col_list{List[ColumnDefinition]} -- column names in the view
+        if_not_exists {bool} -- Whether to override if there is existing view
+    """
+
+    def __init__(
+        self,
+        table_info: TableInfo,
+        column_list: List[ColumnDefinition],
+        if_not_exists: bool = False,
+    ):
+        super().__init__(PlanOprType.CREATE)
+        self._table_info = table_info
+        self._column_list = column_list
+        self._if_not_exists = if_not_exists
+
+    @property
+    def table_info(self):
+        return self._table_info
+
+    @property
+    def if_not_exists(self):
+        return self._if_not_exists
+
+    @property
+    def column_list(self):
+        return self._column_list
+
+    def __str__(self):
+        return "CreateFromSelectPlan(table_info={}, \
+            column_lists={}, \
+            if_not_exists={})".format(
+            self._table_info, self._column_list, self._if_not_exists
+        )
+
+    def __hash__(self) -> int:
+        return hash(
+            (
+                super().__hash__(),
+                self.table_info,
+                self.if_not_exists,
+                tuple(self.column_list),
+            )
+        )

evadb/udfs/chatgpt.py

@@ -35,6 +35,7 @@
     "gpt-3.5-turbo-0301",
 ]
 
+
 class ChatGPT(AbstractUDF):
     """
     Arguments:
@@ -62,12 +63,12 @@ class ChatGPT(AbstractUDF):
         In the above UDF invocation, the 'query' passed would be the user task to generate video summaries, and the
         'content' passed would be the video transcripts that need to be used in order to generate the summary. Since
         no prompt is passed, the default system prompt will be used.
-        
+
         Now assume the user wants to create the video summary in 50 words and in French. Instead of passing these instructions
         along with each query, a prompt can be set as such:
 
             prompt = "Generate your responses in 50 words or less. Also, generate the response in French."
-            cursor.table("video_transcripts").select(f"ChatGPT({question}, text, {prompt})") 
+            cursor.table("video_transcripts").select(f"ChatGPT({question}, text, {prompt})")
 
         In the above invocation, an additional argument is passed as prompt. While the query and content arguments remain
         the same, the 'prompt' argument will be set as a system message in model params.

script/test/test.sh

@@ -105,7 +105,7 @@ fi
 
 if [[ ( "$OSTYPE" != "msys" ) && ( "$MODE" = "NOTEBOOK" || "$MODE" = "ALL" ) ]];
 then 
-    PYTHONPATH=./ python -m pytest --durations=5 --nbmake --overwrite "./tutorials" --capture=sys --tb=short -v --log-level=WARNING --nbmake-timeout=3000 --ignore="tutorials/11-similarity-search-for-motif-mining.ipynb" 
+    PYTHONPATH=./ python -m pytest --durations=5 --nbmake --overwrite "./tutorials" --capture=sys --tb=short -v --log-level=WARNING --nbmake-timeout=3000
     notebook_test_code=$?
     if [ "$notebook_test_code" != "0" ];
     then

tutorials/11-similarity-search-for-motif-mining.ipynb

@@ -776,10 +776,9 @@
    "source": [
     "cursor.drop_table(\"reddit_object_table\").df()\n",
     "create_index_query = \"\"\"\n",
-    "    CREATE MATERIALIZED VIEW IF NOT EXISTS \n",
-    "      reddit_object_table (name, data, bboxes,labels)\n",
+    "    CREATE TABLE IF NOT EXISTS reddit_object_table\n",
     "      AS SELECT name, data, bboxes, labels FROM reddit_dataset\n",
-    "      JOIN LATERAL UNNEST(Yolo(data)) AS Obj(labels, bboxes, scores)\"\"\"\n",
+    "      JOIN LATERAL UNNEST(Yolo(data)) AS Obj(labels, bboxes, scores);\"\"\"\n",
     "cursor.query(create_index_query).df()"
    ]
   },