Add looped mode support for bulk ingestion operation.

osbenchmark/workload/params.py

@@ -699,10 +699,11 @@ def __init__(self, workload, params, **kwargs):
             raise exceptions.InvalidSyntax("'batch-size' must be numeric")
 
         self.ingest_percentage = self.float_param(params, name="ingest-percentage", default_value=100, min_value=0, max_value=100)
+        self.looped = params.get("looped", False)
         self.param_source = PartitionBulkIndexParamSource(self.corpora, self.batch_size, self.bulk_size,
                                                           self.ingest_percentage, self.id_conflicts,
                                                           self.conflict_probability, self.on_conflict,
-                                                          self.recency, self.pipeline, self._params)
+                                                          self.recency, self.pipeline, self.looped, self._params)
 
     def float_param(self, params, name, default_value, min_value, max_value, min_operator=operator.le):
         try:
@@ -749,7 +750,7 @@ def params(self):
 
 class PartitionBulkIndexParamSource:
     def __init__(self, corpora, batch_size, bulk_size, ingest_percentage, id_conflicts, conflict_probability,
-                 on_conflict, recency, pipeline=None, original_params=None):
+                 on_conflict, recency, pipeline=None, looped = False,  original_params=None):
         """
 
         :param corpora: Specification of affected document corpora.
@@ -762,6 +763,7 @@ def __init__(self, corpora, batch_size, bulk_size, ingest_percentage, id_conflic
         :param recency: A number between [0.0, 1.0] indicating whether to bias generation of conflicting ids towards more recent ones.
                         May be None.
         :param pipeline: The name of the ingest pipeline to run.
+        :param looped: Set to True for looped mode where bulk requests are repeated from the beginning when entire corpus was ingested.
         :param original_params: The original dict passed to the parent parameter source.
         """
         self.corpora = corpora
@@ -775,6 +777,7 @@ def __init__(self, corpora, batch_size, bulk_size, ingest_percentage, id_conflic
         self.on_conflict = on_conflict
         self.recency = recency
         self.pipeline = pipeline
+        self.looped = looped
         self.original_params = original_params
         # this is only intended for unit-testing
         self.create_reader = original_params.pop("__create_reader", create_default_reader)
@@ -798,7 +801,11 @@ def params(self):
         # self.internal_params always reads all files. This is necessary to ensure we terminate early in case
         # the user has specified ingest percentage.
         if not self.streaming_ingestion and self.current_bulk == self.total_bulks:
-            raise StopIteration()
+            if self.looped:
+                self.current_bulk = 0
+                self._init_internal_params()
+            else:
+                raise StopIteration()
         self.current_bulk += 1
         return next(self.internal_params)
 

tests/workload/params_test.py

@@ -1174,6 +1174,48 @@ def test_create_with_conflict_probability_not_numeric(self):
 
         self.assertEqual("'conflict-probability' must be numeric", ctx.exception.args[0])
 
+    def test_looped_mode(self):
+        def create_unit_test_reader(*args):
+            return StaticBulkReader(
+                "idx",
+                "doc",
+                bulks=[
+                    ['{"location" : [-0.1485188, 51.5250666]}'],
+                    ['{"location" : [-0.1479949, 51.5252071]}'],
+                ],
+            )
+        corpora = [
+            workload.DocumentCorpus(
+                name="default",
+                documents=[
+                    workload.Documents(
+                        source_format=workload.Documents.SOURCE_FORMAT_BULK,
+                        number_of_documents=2,
+                        target_index="test-idx",
+                        target_type="test-type",
+                    )
+                ],
+            ),
+        ]
+
+        source = params.BulkIndexParamSource(
+            workload=workload.Workload(name="unit-test", corpora=corpora),
+            params={
+                "bulk-size": 2,
+                "looped": True,
+                "__create_reader": create_unit_test_reader,
+            },
+        )
+        partition = source.partition(0, 1)
+        partition.params()
+        # should issue 1 bulk with the size of 2
+        assert partition.total_bulks == 1
+        assert partition.current_bulk == 1
+        partition.params()
+        # should have looped back to the beginning
+        assert partition.total_bulks == 1
+        assert partition.current_bulk == 1
+
 
 class BulkDataGeneratorTests(TestCase):