fix: create index from single document

evadb/catalog/sql_config.py

@@ -21,8 +21,13 @@
 
 from evadb.utils.generic_utils import is_postgres_uri, parse_config_yml
 
+# Permanent identifier column.
 IDENTIFIER_COLUMN = "_row_id"
 
+# Runtime generated column.
+ROW_NUM_COLUMN = "_row_number"
+ROW_NUM_MAGIC = 0xFFFFFFFF
+
 CATALOG_TABLES = [
     "column_catalog",
     "table_catalog",

evadb/executor/create_index_executor.py

@@ -16,7 +16,7 @@
 
 import pandas as pd
 
-from evadb.catalog.sql_config import IDENTIFIER_COLUMN
+from evadb.catalog.sql_config import ROW_NUM_COLUMN
 from evadb.database import EvaDBDatabase
 from evadb.executor.abstract_executor import AbstractExecutor
 from evadb.executor.executor_utils import ExecutorError, handle_vector_store_params
@@ -87,7 +87,7 @@ def _create_index(self):
                     # array. Use zero index to get the actual numpy array.
                     feat = input_batch.column_as_numpy_array(feat_col_name)
 
-                row_id = input_batch.column_as_numpy_array(IDENTIFIER_COLUMN)
+                row_num = input_batch.column_as_numpy_array(ROW_NUM_COLUMN)
 
                 for i in range(len(input_batch)):
                     row_feat = feat[i].reshape(1, -1)
@@ -103,7 +103,7 @@ def _create_index(self):
                         self.index.create(input_dim)
 
                     # Row ID for mapping back to the row.
-                    self.index.add([FeaturePayload(row_id[i], row_feat)])
+                    self.index.add([FeaturePayload(row_num[i], row_feat)])
 
             # Persist index.
             self.index.persist()

evadb/executor/vector_index_scan_executor.py

@@ -16,7 +16,7 @@
 
 import pandas as pd
 
-from evadb.catalog.sql_config import IDENTIFIER_COLUMN
+from evadb.catalog.sql_config import ROW_NUM_COLUMN
 from evadb.database import EvaDBDatabase
 from evadb.executor.abstract_executor import AbstractExecutor
 from evadb.executor.executor_utils import handle_vector_store_params
@@ -27,11 +27,11 @@
 from evadb.utils.logging_manager import logger
 
 
-# Helper function for getting row_id column alias.
-def get_row_id_column_alias(column_list):
+# Helper function for getting row_num column alias.
+def get_row_num_column_alias(column_list):
     for column in column_list:
         alias, col_name = column.split(".")
-        if col_name == IDENTIFIER_COLUMN:
+        if col_name == ROW_NUM_COLUMN:
             return alias
 
 
@@ -74,10 +74,10 @@ def exec(self, *args, **kwargs) -> Iterator[Batch]:
         )
         # todo support queries over distance as well
         # distance_list = index_result.similarities
-        row_id_np = index_result.ids
+        row_num_np = index_result.ids
 
         # Load projected columns from disk and join with search results.
-        row_id_col_name = None
+        row_num_col_name = None
 
         # handle the case where the index_results are less than self.limit_count.value
         num_required_results = self.limit_count.value
@@ -90,14 +90,14 @@ def exec(self, *args, **kwargs) -> Iterator[Batch]:
         res_row_list = [None for _ in range(num_required_results)]
         for batch in self.children[0].exec(**kwargs):
             column_list = batch.columns
-            if not row_id_col_name:
-                row_id_alias = get_row_id_column_alias(column_list)
-                row_id_col_name = "{}.{}".format(row_id_alias, IDENTIFIER_COLUMN)
+            if not row_num_col_name:
+                row_num_alias = get_row_num_column_alias(column_list)
+                row_num_col_name = "{}.{}".format(row_num_alias, ROW_NUM_COLUMN)
 
             # Nested join.
             for _, row in batch.frames.iterrows():
-                for idx, rid in enumerate(row_id_np):
-                    if rid == row[row_id_col_name]:
+                for idx, row_num in enumerate(row_num_np):
+                    if row_num == row[row_num_col_name]:
                         res_row = dict()
                         for col_name in column_list:
                             res_row[col_name] = row[col_name]

evadb/readers/decord_reader.py

@@ -17,6 +17,7 @@
 import numpy as np
 
 from evadb.catalog.catalog_type import VideoColumnName
+from evadb.catalog.sql_config import ROW_NUM_COLUMN
 from evadb.constants import AUDIORATE, IFRAMES
 from evadb.expression.abstract_expression import AbstractExpression
 from evadb.expression.expression_utils import extract_range_list_from_predicate
@@ -126,6 +127,7 @@ def __get_video_frame(self, frame_id):
 
         return {
             VideoColumnName.id.name: frame_id,
+            ROW_NUM_COLUMN: frame_id,
             VideoColumnName.data.name: frame_video,
             VideoColumnName.seconds.name: round(timestamp, 2),
         }
@@ -136,6 +138,7 @@ def __get_audio_frame(self, frame_id):
 
         return {
             VideoColumnName.id.name: frame_id,
+            ROW_NUM_COLUMN: frame_id,
             VideoColumnName.data.name: np.empty(0),
             VideoColumnName.seconds.name: 0.0,
             VideoColumnName.audio.name: frame_audio,

evadb/readers/document/document_reader.py

@@ -15,6 +15,7 @@
 from pathlib import Path
 from typing import Dict, Iterator
 
+from evadb.catalog.sql_config import ROW_NUM_COLUMN
 from evadb.readers.abstract_reader import AbstractReader
 from evadb.readers.document.registry import (
     _lazy_import_loader,
@@ -44,8 +45,14 @@ def _read(self) -> Iterator[Dict]:
             chunk_size=self._chunk_size, chunk_overlap=self._chunk_overlap
         )
 
+        row_num = 0
         for data in loader.load():
             for chunk_id, row in enumerate(
                 langchain_text_splitter.split_documents([data])
             ):
-                yield {"chunk_id": chunk_id, "data": row.page_content}
+                yield {
+                    "chunk_id": chunk_id,
+                    "data": row.page_content,
+                    ROW_NUM_COLUMN: row_num,
+                }
+                row_num += 1

evadb/readers/pdf_reader.py

@@ -14,6 +14,7 @@
 # limitations under the License.
 from typing import Dict, Iterator
 
+from evadb.catalog.sql_config import ROW_NUM_COLUMN
 from evadb.readers.abstract_reader import AbstractReader
 from evadb.utils.generic_utils import try_to_import_fitz
 
@@ -35,6 +36,7 @@ def _read(self) -> Iterator[Dict]:
         doc = fitz.open(self.file_url)
 
         # PAGE ID, PARAGRAPH ID, STRING
+        row_num = 0
         for page_no, page in enumerate(doc):
             blocks = page.get_text("dict")["blocks"]
             # iterate through the text blocks
@@ -51,7 +53,9 @@ def _read(self) -> Iterator[Dict]:
                             if span["text"].strip():
                                 block_string += span["text"]
                     yield {
+                        ROW_NUM_COLUMN: row_num,
                         "page": page_no + 1,
                         "paragraph": paragraph_no + 1,
                         "data": block_string,
                     }
+                    row_num += 1

evadb/storage/document_storage_engine.py

@@ -16,6 +16,7 @@
 from typing import Iterator
 
 from evadb.catalog.models.table_catalog import TableCatalogEntry
+from evadb.catalog.sql_config import ROW_NUM_COLUMN, ROW_NUM_MAGIC
 from evadb.database import EvaDBDatabase
 from evadb.models.storage.batch import Batch
 from evadb.readers.document.document_reader import DocumentReader
@@ -28,7 +29,7 @@ def __init__(self, db: EvaDBDatabase):
 
     def read(self, table: TableCatalogEntry, chunk_params: dict) -> Iterator[Batch]:
         for doc_files in self._rdb_handler.read(self._get_metadata_table(table), 12):
-            for _, (row_id, file_name) in doc_files.iterrows():
+            for _, (row_id, file_name, _) in doc_files.iterrows():
                 system_file_name = self._xform_file_url_to_file_name(file_name)
                 doc_file = Path(table.file_url) / system_file_name
                 # setting batch_mem_size = 1, we need fix it
@@ -38,4 +39,7 @@ def read(self, table: TableCatalogEntry, chunk_params: dict) -> Iterator[Batch]:
                 for batch in reader.read():
                     batch.frames[table.columns[0].name] = row_id
                     batch.frames[table.columns[1].name] = str(file_name)
+                    batch.frames[ROW_NUM_COLUMN] = (
+                        row_id * ROW_NUM_MAGIC + batch.frames[ROW_NUM_COLUMN]
+                    )
                     yield batch

evadb/storage/image_storage_engine.py

@@ -16,6 +16,7 @@
 from typing import Iterator
 
 from evadb.catalog.models.table_catalog import TableCatalogEntry
+from evadb.catalog.sql_config import ROW_NUM_COLUMN
 from evadb.database import EvaDBDatabase
 from evadb.models.storage.batch import Batch
 from evadb.readers.image.opencv_image_reader import CVImageReader
@@ -28,12 +29,13 @@ def __init__(self, db: EvaDBDatabase):
 
     def read(self, table: TableCatalogEntry) -> Iterator[Batch]:
         for image_files in self._rdb_handler.read(self._get_metadata_table(table)):
-            for _, (row_id, file_name) in image_files.iterrows():
+            for _, (row_id, file_name, _) in image_files.iterrows():
                 system_file_name = self._xform_file_url_to_file_name(file_name)
                 image_file = Path(table.file_url) / system_file_name
                 # setting batch_mem_size = 1, we need fix it
                 reader = CVImageReader(str(image_file), batch_mem_size=1)
                 for batch in reader.read():
                     batch.frames[table.columns[0].name] = row_id
                     batch.frames[table.columns[1].name] = str(file_name)
+                    batch.frames[ROW_NUM_COLUMN] = batch.frames[table.columns[0].name]
                     yield batch

evadb/storage/pdf_storage_engine.py

@@ -16,6 +16,7 @@
 from typing import Iterator
 
 from evadb.catalog.models.table_catalog import TableCatalogEntry
+from evadb.catalog.sql_config import ROW_NUM_COLUMN, ROW_NUM_MAGIC
 from evadb.database import EvaDBDatabase
 from evadb.models.storage.batch import Batch
 from evadb.readers.pdf_reader import PDFReader
@@ -28,12 +29,15 @@ def __init__(self, db: EvaDBDatabase):
 
     def read(self, table: TableCatalogEntry) -> Iterator[Batch]:
         for image_files in self._rdb_handler.read(self._get_metadata_table(table), 12):
-            for _, (row_id, file_name) in image_files.iterrows():
+            for _, (row_id, file_name, _) in image_files.iterrows():
                 system_file_name = self._xform_file_url_to_file_name(file_name)
                 image_file = Path(table.file_url) / system_file_name
                 # setting batch_mem_size = 1, we need fix it
                 reader = PDFReader(str(image_file), batch_mem_size=1)
                 for batch in reader.read():
                     batch.frames[table.columns[0].name] = row_id
                     batch.frames[table.columns[1].name] = str(file_name)
+                    batch.frames[ROW_NUM_COLUMN] = (
+                        row_id * ROW_NUM_MAGIC + batch.frames[ROW_NUM_COLUMN]
+                    )
                     yield batch

evadb/storage/sqlite_storage_engine.py

@@ -24,7 +24,7 @@
 from evadb.catalog.models.column_catalog import ColumnCatalogEntry
 from evadb.catalog.models.table_catalog import TableCatalogEntry
 from evadb.catalog.schema_utils import SchemaUtils
-from evadb.catalog.sql_config import IDENTIFIER_COLUMN
+from evadb.catalog.sql_config import IDENTIFIER_COLUMN, ROW_NUM_COLUMN
 from evadb.database import EvaDBDatabase
 from evadb.models.storage.batch import Batch
 from evadb.parser.table_ref import TableInfo
@@ -67,6 +67,7 @@ def _deserialize_sql_row(self, sql_row: dict, columns: List[ColumnCatalogEntry])
                 dict_row[col.name] = self._serializer.deserialize(sql_row[col.name])
             else:
                 dict_row[col.name] = sql_row[col.name]
+        dict_row[ROW_NUM_COLUMN] = dict_row[IDENTIFIER_COLUMN]
         return dict_row
 
     def _try_loading_table_via_reflection(self, table_name: str):
@@ -94,7 +95,11 @@ def create(self, table: TableCatalogEntry, **kwargs):
 
         # During table creation, assume row_id is automatically handled by
         # the sqlalchemy engine.
-        table_columns = [col for col in table.columns if col.name != IDENTIFIER_COLUMN]
+        table_columns = [
+            col
+            for col in table.columns
+            if (col.name != IDENTIFIER_COLUMN and col.name != ROW_NUM_COLUMN)
+        ]
         sqlalchemy_schema = SchemaUtils.xform_to_sqlalchemy_schema(table_columns)
         attr_dict.update(sqlalchemy_schema)
 
@@ -148,12 +153,18 @@ def write(self, table: TableCatalogEntry, rows: Batch):
             # the sqlalchemy engine. Another assumption we make here is the
             # updated data need not to take care of row_id.
             table_columns = [
-                col for col in table.columns if col.name != IDENTIFIER_COLUMN
+                col
+                for col in table.columns
+                if (col.name != IDENTIFIER_COLUMN and col.name != ROW_NUM_COLUMN)
             ]
 
             # Todo: validate the data type before inserting into the table
             for record in rows.frames.values:
-                row_data = {col: record[idx] for idx, col in enumerate(columns)}
+                row_data = {
+                    col: record[idx]
+                    for idx, col in enumerate(columns)
+                    if col != ROW_NUM_COLUMN
+                }
                 data.append(self._dict_to_sql_row(row_data, table_columns))
             self._sql_session.execute(table_to_update.insert(), data)
             self._sql_session.commit()

evadb/storage/video_storage_engine.py

@@ -17,6 +17,7 @@
 from typing import Iterator
 
 from evadb.catalog.models.table_catalog import TableCatalogEntry
+from evadb.catalog.sql_config import ROW_NUM_COLUMN, ROW_NUM_MAGIC
 from evadb.database import EvaDBDatabase
 from evadb.expression.abstract_expression import AbstractExpression
 from evadb.models.storage.batch import Batch
@@ -39,7 +40,7 @@ def read(
         read_video: bool = True,
     ) -> Iterator[Batch]:
         for video_files in self._rdb_handler.read(self._get_metadata_table(table), 12):
-            for _, (row_id, video_file_name) in video_files.iterrows():
+            for _, (row_id, video_file_name, _) in video_files.iterrows():
                 system_file_name = self._xform_file_url_to_file_name(video_file_name)
                 video_file = Path(table.file_url) / system_file_name
                 # increase batch size when reading audio so that
@@ -58,4 +59,7 @@ def read(
                 for batch in reader.read():
                     batch.frames[table.columns[0].name] = row_id
                     batch.frames[table.columns[1].name] = str(video_file_name)
+                    batch.frames[ROW_NUM_COLUMN] = (
+                        row_id * ROW_NUM_MAGIC + batch.frames[ROW_NUM_COLUMN]
+                    )
                     yield batch