X-Git-Url: https://gerrit.fd.io/r/gitweb?p=csit.git;a=blobdiff_plain;f=resources%2Ftools%2Fpresentation%2Finput_data_parser.py;h=9c0e38073ca2f49e190f519e4b837c3a0d90c7a2;hp=37532c83d273c31d68d432ac4c745aa3fbae8c3d;hb=cee3ad0f9cc29ffc67d9c87c58920252671beb21;hpb=2dd27f5a638b5231c0f074ca61e6b67fed9d1faf

diff --git a/resources/tools/presentation/input_data_parser.py b/resources/tools/presentation/input_data_parser.py
index 37532c83d2..9c0e38073c 100644
--- a/resources/tools/presentation/input_data_parser.py
+++ b/resources/tools/presentation/input_data_parser.py
@@ -23,7 +23,6 @@ import multiprocessing
 import os
 import re
 import resource
-import objgraph
 import pandas as pd
 import logging
 
@@ -1189,10 +1188,13 @@ class InputData(object):
 
         return checker.data
 
-    def _download_and_parse_build(self, job, build, repeat, pid=10000):
+    def _download_and_parse_build(self, pid, data_queue, job, build, repeat):
         """Download and parse the input data file.
 
         :param pid: PID of the process executing this method.
+        :param data_queue: Shared memory between processes. Queue which keeps
+            the result data. This data is then read by the main process and used
+            in further processing.
         :param job: Name of the Jenkins job which generated the processed input
             file.
         :param build: Information about the Jenkins build which generated the
@@ -1200,6 +1202,7 @@ class InputData(object):
         :param repeat: Repeat the download specified number of times if not
             successful.
         :type pid: int
+        :type data_queue: multiprocessing.Manager().Queue()
         :type job: str
         :type build: dict
         :type repeat: int
@@ -1280,6 +1283,14 @@ class InputData(object):
                                          format(full_name, repr(err))))
         logs.append(("INFO", "  Done."))
 
+        result = {
+            "data": data,
+            "state": state,
+            "job": job,
+            "build": build
+        }
+        data_queue.put(result)
+
         for level, line in logs:
             if level == "INFO":
                 logging.info(line)
@@ -1292,7 +1303,8 @@ class InputData(object):
             elif level == "WARNING":
                 logging.warning(line)
 
-        return {"data": data, "state": state, "job": job, "build": build}
+        logging.info("Memory allocation: {0:,d}MB".format(
+            resource.getrusage(resource.RUSAGE_SELF).ru_maxrss / 1000))
 
     def download_and_parse_data(self, repeat=1):
         """Download the input data files, parse input data from input files and
@@ -1305,36 +1317,67 @@ class InputData(object):
 
         logging.info("Downloading and parsing input files ...")
 
+        work_queue = multiprocessing.JoinableQueue()
+        manager = multiprocessing.Manager()
+        data_queue = manager.Queue()
+        cpus = multiprocessing.cpu_count()
+
+        workers = list()
+        for cpu in range(cpus):
+            worker = Worker(work_queue,
+                            data_queue,
+                            self._download_and_parse_build)
+            worker.daemon = True
+            worker.start()
+            workers.append(worker)
+            os.system("taskset -p -c {0} {1} > /dev/null 2>&1".
+                      format(cpu, worker.pid))
+
         for job, builds in self._cfg.builds.items():
             for build in builds:
+                work_queue.put((job, build, repeat))
+
+        work_queue.join()
+
+        logging.info("Done.")
+        logging.info("Collecting data:")
+
+        while not data_queue.empty():
+            result = data_queue.get()
+
+            job = result["job"]
+            build_nr = result["build"]["build"]
+            logging.info("  {job}-{build}".format(job=job, build=build_nr))
 
-                result = self._download_and_parse_build(job, build, repeat)
-                build_nr = result["build"]["build"]
+            if result["data"]:
+                data = result["data"]
+                build_data = pd.Series({
+                    "metadata": pd.Series(
+                        data["metadata"].values(),
+                        index=data["metadata"].keys()),
+                    "suites": pd.Series(data["suites"].values(),
+                                        index=data["suites"].keys()),
+                    "tests": pd.Series(data["tests"].values(),
+                                       index=data["tests"].keys())})
 
-                if result["data"]:
-                    data = result["data"]
-                    build_data = pd.Series({
-                        "metadata": pd.Series(
-                            data["metadata"].values(),
-                            index=data["metadata"].keys()),
-                        "suites": pd.Series(data["suites"].values(),
-                                            index=data["suites"].keys()),
-                        "tests": pd.Series(data["tests"].values(),
-                                           index=data["tests"].keys())})
+                if self._input_data.get(job, None) is None:
+                    self._input_data[job] = pd.Series()
+                self._input_data[job][str(build_nr)] = build_data
 
-                    if self._input_data.get(job, None) is None:
-                        self._input_data[job] = pd.Series()
-                    self._input_data[job][str(build_nr)] = build_data
+                self._cfg.set_input_file_name(
+                    job, build_nr, result["build"]["file-name"])
 
-                    self._cfg.set_input_file_name(
-                        job, build_nr, result["build"]["file-name"])
+            self._cfg.set_input_state(job, build_nr, result["state"])
 
-                self._cfg.set_input_state(job, build_nr, result["state"])
+            logging.info("Memory allocation: {0:,d}MB".format(
+                resource.getrusage(resource.RUSAGE_SELF).ru_maxrss / 1000))
 
-                logging.info("ru_maxrss = {0}".format(
-                    resource.getrusage(resource.RUSAGE_SELF).ru_maxrss))
+        del data_queue
 
-                logging.info(objgraph.most_common_types())
+        # Terminate all workers
+        for worker in workers:
+            worker.terminate()
+            worker.join()
 
         logging.info("Done.")