fix: structured data query and auth fixes

- Pass auth token to schema discovery and descriptor generation in
  tg-load-structured-data, fixing 401 errors with IAM enabled
- Fix row query pagination: replace single-page async_execute with
  async_scan that streams pages and applies filters without
  materialising the full result set (OOM on large datasets)
- Add missing filter operators (not, startsWith, endsWith, not_in)
  to row query post-filter matching
- Fall back to scan path when an indexed field is queried with an
  empty string value, since empty index values are not stored
- Revert top-level indexes array support — the current table schema
  overwrites rows with duplicate index values, so only primary_key
  fields are safe to index until the schema is redesigned

trustgraph-cli/trustgraph/cli/load_structured_data.py

@@ -78,7 +78,7 @@ def load_structured_data(
         logger.info("Step 1: Analyzing data to discover best matching schema...")
         
         # Step 1: Auto-discover schema (reuse discover_schema logic)
-        discovered_schema = _auto_discover_schema(api_url, input_file, sample_chars, flow, logger, workspace=workspace)
+        discovered_schema = _auto_discover_schema(api_url, input_file, sample_chars, flow, logger, token=token, workspace=workspace)
         if not discovered_schema:
             logger.error("Failed to discover suitable schema automatically")
             print("❌ Could not automatically determine the best schema for your data.")
@@ -90,7 +90,7 @@ def load_structured_data(
         
         # Step 2: Auto-generate descriptor
         logger.info("Step 2: Generating descriptor configuration...")
-        auto_descriptor = _auto_generate_descriptor(api_url, input_file, discovered_schema, sample_chars, flow, logger, workspace=workspace)
+        auto_descriptor = _auto_generate_descriptor(api_url, input_file, discovered_schema, sample_chars, flow, logger, token=token, workspace=workspace)
         if not auto_descriptor:
             logger.error("Failed to generate descriptor automatically")
             print("❌ Could not automatically generate descriptor configuration.")
@@ -172,7 +172,7 @@ def load_structured_data(
         logger.info(f"Sample chars: {sample_chars} characters")
         
         # Use the helper function to discover schema (get raw response for display)
-        response = _auto_discover_schema(api_url, input_file, sample_chars, flow, logger, return_raw_response=True, workspace=workspace)
+        response = _auto_discover_schema(api_url, input_file, sample_chars, flow, logger, return_raw_response=True, token=token, workspace=workspace)
         
         if response:
             # Debug: print response type and content 
@@ -203,7 +203,7 @@ def load_structured_data(
         # If no schema specified, discover it first
         if not schema_name:
             logger.info("No schema specified, auto-discovering...")
-            schema_name = _auto_discover_schema(api_url, input_file, sample_chars, flow, logger, workspace=workspace)
+            schema_name = _auto_discover_schema(api_url, input_file, sample_chars, flow, logger, token=token, workspace=workspace)
             if not schema_name:
                 print("Error: Could not determine schema automatically.")
                 print("Please specify a schema using --schema-name or run --discover-schema first.")
@@ -213,7 +213,7 @@ def load_structured_data(
             logger.info(f"Target schema: {schema_name}")
         
         # Generate descriptor using helper function
-        descriptor = _auto_generate_descriptor(api_url, input_file, schema_name, sample_chars, flow, logger, workspace=workspace)
+        descriptor = _auto_generate_descriptor(api_url, input_file, schema_name, sample_chars, flow, logger, token=token, workspace=workspace)
         
         if descriptor:
             # Output the generated descriptor
@@ -603,7 +603,7 @@ def _send_to_trustgraph(rows, api_url, flow, batch_size=1000, token=None, worksp
 
 
 # Helper functions for auto mode
-def _auto_discover_schema(api_url, input_file, sample_chars, flow, logger, return_raw_response=False, workspace="default"):
+def _auto_discover_schema(api_url, input_file, sample_chars, flow, logger, return_raw_response=False, token=None, workspace="default"):
     """Auto-discover the best matching schema for the input data
     
     Args:
@@ -626,7 +626,7 @@ def _auto_discover_schema(api_url, input_file, sample_chars, flow, logger, retur
         # Import API modules
         from trustgraph.api import Api
         from trustgraph.api.types import ConfigKey
-        api = Api(api_url, workspace=workspace)
+        api = Api(api_url, token=token, workspace=workspace)
         config_api = api.config()
         
         # Get available schemas
@@ -707,7 +707,7 @@ def _auto_discover_schema(api_url, input_file, sample_chars, flow, logger, retur
         return None
 
 
-def _auto_generate_descriptor(api_url, input_file, schema_name, sample_chars, flow, logger, workspace="default"):
+def _auto_generate_descriptor(api_url, input_file, schema_name, sample_chars, flow, logger, token=None, workspace="default"):
     """Auto-generate descriptor configuration for the discovered schema"""
     try:
         # Read sample data
@@ -717,7 +717,7 @@ def _auto_generate_descriptor(api_url, input_file, schema_name, sample_chars, fl
         # Import API modules
         from trustgraph.api import Api
         from trustgraph.api.types import ConfigKey
-        api = Api(api_url, workspace=workspace)
+        api = Api(api_url, token=token, workspace=workspace)
         config_api = api.config()
         
         # Get schema definition

trustgraph-flow/trustgraph/query/rows/cassandra/service.py

@@ -24,7 +24,7 @@ from .... schema import RowsQueryRequest, RowsQueryResponse, GraphQLError
 from .... schema import Error, RowSchema, Field as SchemaField
 from .... base import FlowProcessor, ConsumerSpec, ProducerSpec
 from .... base.cassandra_config import add_cassandra_args, resolve_cassandra_config
-from .... tables.cassandra_async import async_execute
+from .... tables.cassandra_async import async_execute, async_execute_paged, async_scan
 
 from ... graphql import GraphQLSchemaBuilder, SortDirection
 
@@ -180,7 +180,7 @@ class Processor(FlowProcessor):
                         description=field_def.get("description", ""),
                         required=field_def.get("required", False),
                         enum_values=field_def.get("enum", []),
-                        indexed=field_def.get("indexed", False)
+                        indexed=field_def.get("indexed", False),
                     )
                     fields.append(field)
 
@@ -232,6 +232,8 @@ class Processor(FlowProcessor):
         for index_name in index_names:
             if index_name in filters:
                 value = filters[index_name]
+                if value == "" or value is None:
+                    continue
                 # Single field index -> single element list
                 index_value = [str(value)]
                 return (index_name, index_value)
@@ -282,11 +284,13 @@ class Processor(FlowProcessor):
                 query += f" LIMIT {limit}"
 
             try:
-                rows = await async_execute(self.session, query, params)
+                pages = await async_execute_paged(
-                for row in rows:
+                    self.session, query, params
-                    # Convert data map to dict with proper field names
+                )
-                    row_dict = dict(row.data) if row.data else {}
+                for page in pages:
-                    results.append(row_dict)
+                    for row in page:
+                        row_dict = dict(row.data) if row.data else {}
+                        results.append(row_dict)
             except Exception as e:
                 logger.error(f"Failed to query rows: {e}", exc_info=True)
                 raise
@@ -308,8 +312,6 @@ class Processor(FlowProcessor):
             # Query using the first index (arbitrary choice for scan)
             primary_index = index_names[0]
 
-            # We need to scan all values for this index
-            # This requires ALLOW FILTERING or a different approach
             query = f"""
             SELECT data, source FROM {safe_keyspace}.rows
             WHERE collection = %s
@@ -320,17 +322,18 @@ class Processor(FlowProcessor):
             params = [collection, schema_name, primary_index]
 
             try:
-                rows = await async_execute(self.session, query, params)
+                def row_filter(row):
-
-                for row in rows:
                     row_dict = dict(row.data) if row.data else {}
+                    return self._matches_filters(row_dict, filters, row_schema)
 
-                    # Apply post-filters
+                matched_rows = await async_scan(
-                    if self._matches_filters(row_dict, filters, row_schema):
+                    self.session, query, params,
-                        results.append(row_dict)
+                    row_filter=row_filter,
-
+                    limit=limit,
-                        if limit and len(results) >= limit:
+                )
-                            break
+                for row in matched_rows:
+                    row_dict = dict(row.data) if row.data else {}
+                    results.append(row_dict)
 
             except Exception as e:
                 logger.error(f"Failed to scan rows: {e}", exc_info=True)
@@ -363,7 +366,7 @@ class Processor(FlowProcessor):
             # Parse filter key for operator
             if '_' in filter_key:
                 parts = filter_key.rsplit('_', 1)
-                if parts[1] in ['gt', 'gte', 'lt', 'lte', 'contains', 'in']:
+                if parts[1] in ['gt', 'gte', 'lt', 'lte', 'contains', 'in', 'not', 'startsWith', 'endsWith', 'not_in']:
                     field_name = parts[0]
                     operator = parts[1]
                 else:
@@ -400,6 +403,18 @@ class Processor(FlowProcessor):
                 elif operator == 'in':
                     if str(row_value) not in [str(v) for v in filter_value]:
                         return False
+                elif operator == 'not':
+                    if str(row_value) == str(filter_value):
+                        return False
+                elif operator == 'startsWith':
+                    if not str(row_value).startswith(str(filter_value)):
+                        return False
+                elif operator == 'endsWith':
+                    if not str(row_value).endswith(str(filter_value)):
+                        return False
+                elif operator == 'not_in':
+                    if str(row_value) in [str(v) for v in filter_value]:
+                        return False
             except (ValueError, TypeError):
                 return False
 

trustgraph-flow/trustgraph/storage/rows/cassandra/write.py

@@ -172,7 +172,7 @@ class Processor(CollectionConfigHandler, FlowProcessor):
                         description=field_def.get("description", ""),
                         required=field_def.get("required", False),
                         enum_values=field_def.get("enum", []),
-                        indexed=field_def.get("indexed", False)
+                        indexed=field_def.get("indexed", False),
                     )
                     fields.append(field)
 

trustgraph-flow/trustgraph/tables/cassandra_async.py

@@ -80,14 +80,14 @@ def _set_exception_if_pending(fut, exc):
         fut.set_exception(exc)
 
 
-async def async_execute_paged(session, query, parameters=None, fetch_size=100):
+async def async_execute_paged(session, query, parameters=None, fetch_size=5000):
     """Execute a CQL query with page-by-page iteration.
 
     Uses synchronous session.execute() inside run_in_executor so that
     the driver's ResultSet paging works correctly without materialising
     the entire result set in memory.
 
-    Yields one page of rows at a time (as a list).
+    Returns all pages as a list of lists.
     """
     loop = asyncio.get_running_loop()
 
@@ -111,3 +111,50 @@ async def async_execute_paged(session, query, parameters=None, fetch_size=100):
     return await loop.run_in_executor(
         None, _fetch_all_pages
     )
+
+
+async def async_scan(
+    session, query, parameters=None, row_filter=None,
+    limit=None, fetch_size=5000,
+):
+    """Scan a CQL query page-by-page, applying a filter and limit.
+
+    Only matching rows accumulate in memory.  Each page is discarded
+    after processing, so peak memory is bounded by fetch_size plus
+    the number of matching rows (capped by limit).
+
+    Args:
+        session: cassandra.cluster.Session
+        query: CQL statement string
+        parameters: bind params
+        row_filter: callable(row) -> bool, or None to accept all
+        limit: max results to return, or None for unlimited
+        fetch_size: rows per Cassandra page fetch
+
+    Returns:
+        List of matching rows.
+    """
+    loop = asyncio.get_running_loop()
+
+    if isinstance(query, str):
+        stmt = SimpleStatement(query, fetch_size=fetch_size)
+    else:
+        stmt = query
+        stmt.fetch_size = fetch_size
+
+    def _scan():
+        results = []
+        result_set = session.execute(stmt, parameters)
+        while True:
+            for row in result_set.current_rows:
+                if row_filter is None or row_filter(row):
+                    results.append(row)
+                    if limit and len(results) >= limit:
+                        return results
+            if result_set.has_more_pages:
+                result_set.fetch_next_page()
+            else:
+                break
+        return results
+
+    return await loop.run_in_executor(None, _scan)