Use async runners if needed

Due to elastic/rally#852 we will implement a compatibility layer in the
current load generator that will also use the asyncio API and thus
requires custom runners to be registered differently (by specifying
`async_runner=True`). Rally's runner registry will also expose a new
attribute `async_runner` that is set to `True` if Rally requires runners
to be registered as described above.

With this commit we introduce a (temporary) compatibility layer for all
custom runners that allows older Rally versions to work with the classic
runners and newer Rally versions with the async runners.

Relates elastic/rally#852

Makefile

@@ -29,10 +29,10 @@ PYENV_PREREQ_HELP = "\033[0;31mIMPORTANT\033[0m: please add \033[0;31meval \"\$$
 VE_MISSING_HELP = "\033[0;31mIMPORTANT\033[0m: Couldn't find $(PWD)/$(VENV_NAME); have you executed make venv-create?\033[0m\n"
 
 prereq: make-requirements.txt
-	pyenv install --skip-existing $(PY35)
 	pyenv install --skip-existing $(PY36)
 	pyenv install --skip-existing $(PY37)
-	pyenv global system $(PY35) $(PY36) $(PY37)
+	pyenv install --skip-existing $(PY38)
+	pyenv local $(PY36) $(PY37) $(PY38)
 	@# Ensure all Python versions are registered for this project
 	@awk -F'=' '{print $$2}' make-requirements.txt > .python-version
 	-@ printf $(PYENV_PREREQ_HELP)

eventdata/runners/deleteindex_runner.py

@@ -18,7 +18,8 @@
 
 from fnmatch import fnmatch
 
-def deleteindex(es, params):
+
+async def deleteindex_async(es, params):
     """
     Deletes all indices in Elasticsearch matching either the specified index pattern or
     the suffix of the index against a more complex pattern.
@@ -65,13 +66,77 @@ def get_suffix(name, separator):
     suffix_separator = params.get('suffix_separator', '-')
 
     if max_indices:
-        indices = es.cat.indices(h='index').split("\n")
+        indices = await es.cat.indices(h='index').split("\n")
         indices_by_suffix = {get_suffix(idx, suffix_separator): idx
             for idx in indices
             if fnmatch(idx, index_pattern) and
             get_suffix(idx, suffix_separator) is not None
         }
 
+        sorted_suffixes = sorted(list(indices_by_suffix.keys()))
+        if len(sorted_suffixes) > max_indices:
+            indices_to_delete = ",".join([indices_by_suffix[key] for key in sorted_suffixes[:(len(sorted_suffixes)-max_indices)]])
+            await es.indices.delete(indices_to_delete)
+    else:
+        await es.indices.delete(index=index_pattern)
+
+    return 1, "ops"
+
+
+def deleteindex(es, params):
+    """
+    Deletes all indices in Elasticsearch matching either the specified index pattern or
+    the suffix of the index against a more complex pattern.
+
+    :param es: Specifies the index pattern to delete. Defaults to 'elasticlogs-*'
+    :type es: str
+    :param params: Parameter hash containing one of the keys documented below.
+    :type params: dict
+
+        "index_pattern"        - Mandatory.
+                                 Specifies the index pattern to delete.
+        "max_indices"          - Optional.
+                                 int specifying how many rolled over indices to retain at max.
+                                 The elibigle indices need to satisfy `index-pattern`.
+                                 'suffix_separator' is used to retrieve the integer suffixes to calculate indices to delete.
+
+                                 Example:
+                                    For the indices: 'elasticlogs-000001', 'elasticlogs-000002', ... 000011
+                                    (index currently written to is 'elasticlogs-000011')
+
+                                    using:
+                                        suffix_separator='-' and
+                                        max_indices=8
+
+                                    will result in deleting indices 'elasticlogs-000001' and 'elasticlogs-000002'
+        "suffix_separator"     - Defaults to '-'. Used only when 'max_indices' is specified.
+                                 Specifies string separator used to extract the index suffix, e.g. '-'.
+
+
+    """
+    def get_suffix(name, separator):
+        if separator in name:
+            name_parts = name.split(separator)
+            if len(name_parts) > 1:
+                try:
+                    return int(name_parts[-1])
+                except ValueError:
+                    # TODO: log that suffix is not integer
+                    return None
+        return None
+
+    index_pattern = params['index_pattern']
+    max_indices = params.get('max_indices', None)
+    suffix_separator = params.get('suffix_separator', '-')
+
+    if max_indices:
+        indices = es.cat.indices(h='index').split("\n")
+        indices_by_suffix = {get_suffix(idx, suffix_separator): idx
+                             for idx in indices
+                             if fnmatch(idx, index_pattern) and
+                             get_suffix(idx, suffix_separator) is not None
+                             }
+
         sorted_suffixes = sorted(list(indices_by_suffix.keys()))
         if len(sorted_suffixes) > max_indices:
             indices_to_delete = ",".join([indices_by_suffix[key] for key in sorted_suffixes[:(len(sorted_suffixes)-max_indices)]])

eventdata/runners/fieldstats_runner.py

@@ -20,6 +20,69 @@
 import logging
 
 
+async def fieldstats_async(es, params):
+    """
+    Looks up minimum and maximum values for a specified field for an index pattern and stores
+    this information in a global variable that can be accessed by other components of the track.
+
+    It expects a parameter dictionary with the following keys:
+
+    * index_pattern (mandatory): Index pattern statistics are retrieved for.
+    * fieldname (optional): Field to extract statistics for. Defaults to "@timestamp".
+
+    """
+    index_pattern = params["index_pattern"]
+    field_name = params.get("fieldname", "@timestamp")
+    ignore_throttled = params.get("ignore_throttled", True)
+
+    if ignore_throttled:
+        query_params = {}
+    else:
+        query_params = {"ignore_throttled": "false"}
+
+    result = await es.search(index=index_pattern,
+                             body={
+                                 "query": {
+                                     "match_all": {}
+                                 },
+                                 "size": 0,
+                                 "aggs": {
+                                     "maxval": {
+                                         "max": {
+                                             "field": field_name
+                                         }
+                                     },
+                                     "minval": {
+                                         "min": {
+                                             "field": field_name
+                                         }
+                                     }
+                                 }
+                             },
+                             params=query_params)
+
+    hits = result["hits"]["total"]
+    # ES 7.0+
+    if isinstance(hits, dict):
+        total_hits = hits["value"]
+    else:
+        total_hits = hits
+
+    if total_hits > 0:
+        key = "{}_{}".format(index_pattern, field_name)
+        min_field_value = int(result["aggregations"]["minval"]["value"])
+        max_field_value = int(result["aggregations"]["maxval"]["value"])
+        gs.global_fieldstats[key] = {
+            "max": max_field_value,
+            "min": min_field_value
+        }
+        logger = logging.getLogger("track.eventdata.fieldstats")
+        logger.info("Identified statistics for field '%s' in '%s'. Min: %d, Max: %d",
+                    field_name, index_pattern, min_field_value, max_field_value)
+    else:
+        raise AssertionError("No matching data found for field '{}' in pattern '{}'.".format(field_name, index_pattern))
+
+
 def fieldstats(es, params):
     """
     Looks up minimum and maximum values for a specified field for an index pattern and stores

eventdata/runners/indicesstats_runner.py

@@ -23,6 +23,65 @@
 
 logger = logging.getLogger("track.eventdata")
 
+
+async def indicesstats_async(es, params):
+    """
+    Retrieves index stats for an index or index pattern.
+
+    It expects the parameter hash to contain the following keys:
+        "index_pattern" - Index pattern that storage statistics are retrieved for.
+    """
+    index_pattern = params['index_pattern']
+    response = {
+        "weight": 1,
+        "unit": "ops",
+        "index_pattern": index_pattern
+    }
+
+    try:
+        result = await es.indices.stats(index=index_pattern, metric='store,docs,segments')
+
+        if result['_all']:
+            a = result['_all']
+
+            if a['primaries']['docs']['count']:
+                response['primary_doc_count'] = a['primaries']['docs']['count']
+
+            if a['total']['docs']['count']:
+                response['total_doc_count'] = a['total']['docs']['count']
+
+            if a['primaries']['store']['size_in_bytes']:
+                response['primary_size_bytes'] = a['primaries']['store']['size_in_bytes']
+
+            if a['total']['store']['size_in_bytes']:
+                response['total_size_bytes'] = a['total']['store']['size_in_bytes']
+
+            if a['primaries']['segments']['count']:
+                response['primary_segment_count'] = a['primaries']['segments']['count']
+
+            if a['total']['segments']['count']:
+                response['total_segment_count'] = a['total']['segments']['count']
+
+            if a['primaries']['segments']['memory_in_bytes']:
+                response['primary_segments_memory_in_bytes'] = a['primaries']['segments']['memory_in_bytes']
+
+            if a['total']['segments']['memory_in_bytes']:
+                response['total_segment_memory_in_bytes'] = a['total']['segments']['memory_in_bytes']
+
+            if a['primaries']['segments']['terms_memory_in_bytes']:
+                response['primary_segment_terms_memory_in_bytes'] = a['primaries']['segments']['terms_memory_in_bytes']
+
+            if a['total']['segments']['terms_memory_in_bytes']:
+                response['total_segment_terms_memory_in_bytes'] = a['total']['segments']['terms_memory_in_bytes']
+
+        if logger.isEnabledFor(logging.DEBUG):
+            logger.debug("Indices stats for {} => {}".format(index_pattern, json.dumps(result)))
+    except elasticsearch.TransportError as e:
+        logger.info("[indicesstats_runner] Error: {}".format(e))
+
+    return response
+
+
 def indicesstats(es, params):
     """
     Retrieves index stats for an index or index pattern.

eventdata/runners/kibana_runner.py

@@ -23,6 +23,60 @@
 logger = logging.getLogger("track.eventdata")
 
 
+async def kibana_async(es, params):
+    """
+    Simulates Kibana msearch dashboard queries.
+
+    It expects the parameter hash to contain the following keys:
+        "body"      - msearch request body representing the Kibana dashboard in the  form of an array of dicts.
+        "meta_data" - Dictionary containing meta data information to be carried through into metrics.
+    """
+    request = params["body"]
+    meta_data = params["meta_data"]
+
+    if meta_data["debug"]:
+        logger.info("Request:\n=====\n{}\n=====".format(json.dumps(request)))
+
+    visualisations = int(len(request) / 2)
+
+    response = {}
+
+    for key in meta_data.keys():
+        response[key] = meta_data[key]
+
+    response["weight"] = 1
+    response["unit"] = "ops"
+    response["visualisation_count"] = visualisations
+
+    if "pre_filter_shard_size" in meta_data:
+        result = await es.msearch(body=request, params={"pre_filter_shard_size": meta_data["pre_filter_shard_size"]})
+    else:
+        result = await es.msearch(body=request)
+
+    sum_hits = 0
+    max_took = 0
+    for r in result["responses"]:
+        hits = r.get("hits", {}).get("total", 0)
+        if isinstance(hits, dict):
+            sum_hits += hits["value"]
+        else:
+            sum_hits += hits
+        max_took = max(max_took, r["took"])
+
+    # use the request's took if possible but approximate it using the maximum of all responses
+    response["took"] = result.get("took", max_took)
+    response["hits"] = sum_hits
+
+    if meta_data["debug"]:
+        for r in result["responses"]:
+            # clear hits otherwise we'll spam the log
+            r["hits"]["hits"] = []
+            r["aggregations"] = {}
+        logger.info("Response (excluding specific hits):\n=====\n{}\n=====".format(json.dumps(result)))
+
+    return response
+
+
 def kibana(es, params):
     """
     Simulates Kibana msearch dashboard queries.

eventdata/runners/nodestorage_runner.py

@@ -25,6 +25,50 @@
 BYTES_PER_TB = 1024 * 1024 * 1024 * 1024
 
 
+async def nodestorage_async(es, params):
+    """
+    Calculates the total data volume in the cluster as well as average volume per data node.
+
+    It takes no parameters.
+    """
+    response = {
+        "weight": 1,
+        "unit": "ops"
+    }
+
+    try:
+        # get number of data nodes
+        node_role_list = await es.cat.nodes(h="node.role")
+
+        data_node_count = 0
+
+        for node_role in node_role_list:
+            if 'd' in node_role:
+                data_node_count += 1
+
+        result = await es.indices.stats(index='*', metric='store')
+        total_data_size = 0
+
+        if result['_all']:
+            if result['_all']['total']['store']['size_in_bytes']:
+                total_data_size = result['_all']['total']['store']['size_in_bytes']
+
+        total_data_size_tb = float(total_data_size) / BYTES_PER_TB
+
+        volume_per_data_node = int(total_data_size / data_node_count)
+        volume_per_data_node_tb = total_data_size_tb / data_node_count
+
+        response['total_data_volume_bytes'] = total_data_size
+        response['total_data_volume_tb'] = total_data_size_tb
+        response['average_data_volume_per_node_bytes'] = volume_per_data_node
+        response['average_data_volume_per_node_tb'] = volume_per_data_node_tb
+
+    except elasticsearch.TransportError as e:
+        logger.info("[nodestorage_runner] Error: {}".format(e))
+
+    return response
+
+
 def nodestorage(es, params):
     """
     Calculates the total data volume in the cluster as well as average volume per data node.

eventdata/runners/rollover_runner.py

@@ -16,6 +16,18 @@
 # under the License.
 
 
+async def rollover_async(es, params):
+    """
+    Runs a rollover operation against Elasticsearch.
+
+    It expects the parameter hash to contain a key "alias" specifying the alias to rollover
+    as well as a key "body" containing the actual rollover request and associated conditions.
+
+    """
+    await es.indices.rollover(alias=params["alias"], body=params["body"])
+    return 1, "ops"
+
+
 def rollover(es, params):
     """
     Runs a rollover operation against Elasticsearch.