diff --git a/zipline/pipeline/loaders/blaze/core.py b/zipline/pipeline/loaders/blaze/core.py
index d17612a4..03eb46d8 100644
--- a/zipline/pipeline/loaders/blaze/core.py
+++ b/zipline/pipeline/loaders/blaze/core.py
@@ -904,44 +904,12 @@ class BlazeLoader(dict):
             q : Expr
                 The query to run.
             """
-            def lower_for_col(column):
-                pred = e[TS_FIELD_NAME] <= lower_dt
-                colname = column.name
-                schema = e[colname].schema.measure
-                if isinstance(schema, Option):
-                    pred &= e[colname].notnull()
-                    schema = schema.ty
-                if schema in floating:
-                    pred &= ~e[colname].isnan()
-
-                filtered = e[pred]
-                lower = filtered[TS_FIELD_NAME].max()
-                if have_sids:
-                    # If we have sids, then we need to take the earliest of the
-                    # greatest date that has a non-null value by sid.
-                    lower = bz.by(
-                        filtered[SID_FIELD_NAME],
-                        timestamp=lower,
-                    ).timestamp.min()
-                return lower
-
-            lower = odo(
-                reduce(
-                    bz.least,
-                    map(lower_for_col, columns),
-                ),
-                pd.Timestamp,
-                **odo_kwargs
-            )
-            if lower is pd.NaT:
-                lower = lower_dt
             return e[
-                (e[TS_FIELD_NAME] >= lower) &
                 (e[TS_FIELD_NAME] <= upper_dt)
             ][added_query_fields + list(map(getname, columns))]
 
         def collect_expr(e):
-            """Execute and merge all of the per-column subqueries.
+            """Materialize the expression as a dataframe.
 
             Parameters
             ----------