chore: avoid bq storage API deadlock by setting max_results. (#1355)

Author: Genesis929

scripts/tpch_result_verify.py

@@ -772,7 +772,7 @@ def verify(query_num=None):
                 file_content = file.read()
 
                 file_content = re.sub(
-                    r"next\((\w+)\.to_pandas_batches\(\)\)",
+                    r"next\((\w+)\.to_pandas_batches\((.*?)\)\)",
                     r"return \1.to_pandas()",
                     file_content,
                 )

third_party/bigframes_vendored/tpch/queries/q1.py

@@ -39,4 +39,4 @@ def q(project_id: str, dataset_id: str, session: bigframes.Session):
         ["L_RETURNFLAG", "L_LINESTATUS"]
     )
 
-    next(result.to_pandas_batches())
+    next(result.to_pandas_batches(max_results=1500))

third_party/bigframes_vendored/tpch/queries/q10.py

@@ -76,4 +76,4 @@ def q(project_id: str, dataset_id: str, session: bigframes.Session):
         .head(20)
     )
 
-    next(q_final.to_pandas_batches())
+    next(q_final.to_pandas_batches(max_results=1500))

third_party/bigframes_vendored/tpch/queries/q11.py

@@ -43,4 +43,4 @@ def q(project_id: str, dataset_id: str, session: bigframes.Session):
 
     result_df = result_df.sort_values(by="VALUE", ascending=False)
 
-    next(result_df.to_pandas_batches())
+    next(result_df.to_pandas_batches(max_results=1500))

third_party/bigframes_vendored/tpch/queries/q12.py

@@ -46,4 +46,4 @@ def q(project_id: str, dataset_id: str, session: bigframes.Session):
 
     agg_results = typing.cast(bpd.DataFrame, agg_results).sort_values("L_SHIPMODE")
 
-    next(agg_results.to_pandas_batches())
+    next(agg_results.to_pandas_batches(max_results=1500))

third_party/bigframes_vendored/tpch/queries/q13.py

@@ -34,4 +34,4 @@ def q(project_id: str, dataset_id: str, session: bigframes.Session):
         ["CUSTDIST", "C_COUNT"], ascending=[False, False]
     )
 
-    next(q_final.to_pandas_batches())
+    next(q_final.to_pandas_batches(max_results=1500))

third_party/bigframes_vendored/tpch/queries/q14.py

@@ -42,4 +42,4 @@ def q(project_id: str, dataset_id: str, session: bigframes.Session):
         .to_frame(name="PROMO_REVENUE")
     )
 
-    next(promo_revenue_percent.to_pandas_batches())
+    next(promo_revenue_percent.to_pandas_batches(max_results=1500))

third_party/bigframes_vendored/tpch/queries/q15.py

@@ -50,4 +50,4 @@ def q(project_id: str, dataset_id: str, session: bigframes.Session):
     q_final = max_revenue_suppliers[
         ["S_SUPPKEY", "S_NAME", "S_ADDRESS", "S_PHONE", "TOTAL_REVENUE"]
     ].sort_values("S_SUPPKEY")
-    next(q_final.to_pandas_batches())
+    next(q_final.to_pandas_batches(max_results=1500))

third_party/bigframes_vendored/tpch/queries/q16.py

@@ -47,4 +47,4 @@ def q(project_id: str, dataset_id: str, session: bigframes.Session):
         ascending=[False, True, True, True],
     )
 
-    next(q_final.to_pandas_batches())
+    next(q_final.to_pandas_batches(max_results=1500))

third_party/bigframes_vendored/tpch/queries/q17.py

@@ -37,4 +37,4 @@ def q(project_id: str, dataset_id: str, session: bigframes.Session):
         (q_final[["L_EXTENDEDPRICE"]].sum() / 7.0).round(2).to_frame(name="AVG_YEARLY")
     )
 
-    next(q_final.to_pandas_batches())
+    next(q_final.to_pandas_batches(max_results=1500))