Parallel queries experiment

Refs #1576

datasette/database.py

@@ -256,18 +256,26 @@ class Database:
         # Try to get counts for each table, $limit timeout for each count
         counts = {}
         for table in await self.table_names():
-            try:
-                table_count = (
-                    await self.execute(
-                        f"select count(*) from [{table}]",
-                        custom_time_limit=limit,
-                    )
-                ).rows[0][0]
-                counts[table] = table_count
-            # In some cases I saw "SQL Logic Error" here in addition to
-            # QueryInterrupted - so we catch that too:
-            except (QueryInterrupted, sqlite3.OperationalError, sqlite3.DatabaseError):
-                counts[table] = None
+            print(table.lower())
+            if table.lower() == "knn":
+                counts[table] = 0
+            else:
+                try:
+                    table_count = (
+                        await self.execute(
+                            f"select count(*) from [{table}]",
+                            custom_time_limit=limit,
+                        )
+                    ).rows[0][0]
+                    counts[table] = table_count
+                # In some cases I saw "SQL Logic Error" here in addition to
+                # QueryInterrupted - so we catch that too:
+                except (
+                    QueryInterrupted,
+                    sqlite3.OperationalError,
+                    sqlite3.DatabaseError,
+                ):
+                    counts[table] = None
         if not self.is_mutable:
             self._cached_table_counts = counts
         return counts
@@ -318,7 +326,7 @@ class Database:
             return explicit_label_column
         column_names = await self.execute_fn(lambda conn: table_columns(conn, table))
         # Is there a name or title column?
-        name_or_title = [c for c in column_names if c.lower() in ("name", "title")]
+        name_or_title = [c for c in column_names if c.lower() in ("name", "title", "display_name", "displayname")]
         if name_or_title:
             return name_or_title[0]
         # If a table has two columns, one of which is ID, then label_column is the other one

datasette/url_builder.py

@@ -7,12 +7,18 @@ class Urls:
         self.ds = ds
 
     def path(self, path, format=None):
+        print(
+            "Urls.path called with: {} (PrefixedUrlString = {})".format(
+                path, isinstance(path, PrefixedUrlString)
+            )
+        )
         if not isinstance(path, PrefixedUrlString):
             if path.startswith("/"):
                 path = path[1:]
             path = self.ds.setting("base_url") + path
         if format is not None:
             path = path_with_format(path=path, format=format)
+        print("  returning", path)
         return PrefixedUrlString(path)
 
     def instance(self, format=None):

datasette/views/table.py

@@ -1,3 +1,4 @@
+import asyncio
 import urllib
 import itertools
 import json
@@ -26,6 +27,7 @@ from datasette.utils import (
 )
 from datasette.utils.asgi import BadRequest, NotFound
 from datasette.filters import Filters
+from datasette import tracer
 from .base import DataView, DatasetteError, ureg
 from .database import QueryView
 
@@ -616,44 +618,37 @@ class TableView(RowTableShared):
         if request.args.get("_timelimit"):
             extra_args["custom_time_limit"] = int(request.args.get("_timelimit"))
 
-        # Execute the main query!
-        results = await db.execute(sql, params, truncate=True, **extra_args)
+        async def execute_count():
+            # Calculate the total count for this query
+            filtered_table_rows_count = None
+            if (
+                not db.is_mutable
+                and self.ds.inspect_data
+                and count_sql == f"select count(*) from {table} "
+            ):
+                # We can use a previously cached table row count
+                try:
+                    filtered_table_rows_count = self.ds.inspect_data[database][
+                        "tables"
+                    ][table]["count"]
+                except KeyError:
+                    pass
 
-        # Calculate the total count for this query
-        filtered_table_rows_count = None
-        if (
-            not db.is_mutable
-            and self.ds.inspect_data
-            and count_sql == f"select count(*) from {table} "
-        ):
-            # We can use a previously cached table row count
-            try:
-                filtered_table_rows_count = self.ds.inspect_data[database]["tables"][
-                    table
-                ]["count"]
-            except KeyError:
-                pass
+            if count_sql and filtered_table_rows_count is None and not nocount:
+                try:
+                    count_rows = list(await db.execute(count_sql, from_sql_params))
+                    filtered_table_rows_count = count_rows[0][0]
+                except QueryInterrupted:
+                    pass
 
-        # Otherwise run a select count(*) ...
-        if count_sql and filtered_table_rows_count is None and not nocount:
-            try:
-                count_rows = list(await db.execute(count_sql, from_sql_params))
-                filtered_table_rows_count = count_rows[0][0]
-            except QueryInterrupted:
-                pass
+            return filtered_table_rows_count
 
-        # Faceting
-        if not self.ds.setting("allow_facet") and any(
-            arg.startswith("_facet") for arg in request.args
-        ):
-            raise BadRequest("_facet= is not allowed")
+        filtered_table_rows_count = await execute_count()
 
         # pylint: disable=no-member
         facet_classes = list(
             itertools.chain.from_iterable(pm.hook.register_facet_classes())
         )
-        facet_results = {}
-        facets_timed_out = []
         facet_instances = []
         for klass in facet_classes:
             facet_instances.append(
@@ -669,33 +664,59 @@ class TableView(RowTableShared):
                 )
             )
 
-        if not nofacet:
-            for facet in facet_instances:
-                (
-                    instance_facet_results,
-                    instance_facets_timed_out,
-                ) = await facet.facet_results()
-                for facet_info in instance_facet_results:
-                    base_key = facet_info["name"]
-                    key = base_key
-                    i = 1
-                    while key in facet_results:
-                        i += 1
-                        key = f"{base_key}_{i}"
-                    facet_results[key] = facet_info
-                facets_timed_out.extend(instance_facets_timed_out)
+        async def execute_suggested_facets():
+            # Calculate suggested facets
+            suggested_facets = []
+            if (
+                self.ds.setting("suggest_facets")
+                and self.ds.setting("allow_facet")
+                and not _next
+                and not nofacet
+                and not nosuggest
+            ):
+                for facet in facet_instances:
+                    suggested_facets.extend(await facet.suggest())
+            return suggested_facets
 
-        # Calculate suggested facets
-        suggested_facets = []
-        if (
-            self.ds.setting("suggest_facets")
-            and self.ds.setting("allow_facet")
-            and not _next
-            and not nofacet
-            and not nosuggest
-        ):
-            for facet in facet_instances:
-                suggested_facets.extend(await facet.suggest())
+        async def execute_facets():
+            facet_results = {}
+            facets_timed_out = []
+            if not self.ds.setting("allow_facet") and any(
+                arg.startswith("_facet") for arg in request.args
+            ):
+                raise BadRequest("_facet= is not allowed")
+
+            if not nofacet:
+                for facet in facet_instances:
+                    (
+                        instance_facet_results,
+                        instance_facets_timed_out,
+                    ) = await facet.facet_results()
+                    for facet_info in instance_facet_results:
+                        base_key = facet_info["name"]
+                        key = base_key
+                        i = 1
+                        while key in facet_results:
+                            i += 1
+                            key = f"{base_key}_{i}"
+                        facet_results[key] = facet_info
+                    facets_timed_out.extend(instance_facets_timed_out)
+
+            return facet_results, facets_timed_out
+
+        # Execute the main query, facets and facet suggestions in parallel:
+        with tracer.trace_child_tasks():
+            (
+                results,
+                suggested_facets,
+                (facet_results, facets_timed_out),
+            ) = await asyncio.gather(
+                db.execute(sql, params, truncate=True, **extra_args),
+                execute_suggested_facets(),
+                execute_facets(),
+            )
+
+        results = await db.execute(sql, params, truncate=True, **extra_args)
 
         # Figure out columns and rows for the query
         columns = [r[0] for r in results.description]