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592
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1 import unittest
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2 import time
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3 import os
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4 import threading
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5 from helpers import OrthancTestCase, Helpers
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6
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598
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7 from orthanc_api_client import OrthancApiClient, ChangeType
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8 from orthanc_api_client import helpers as OrthancHelpers
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9
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592
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10 from orthanc_tools import OrthancTestDbPopulator
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11
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12 import pathlib
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13 import subprocess
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14 import glob
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15 here = pathlib.Path(__file__).parent.resolve()
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16
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17
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18 def worker_upload_folder(orthanc_root_url: str, folder: str, repeat: int, worker_id: int):
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19 o = OrthancApiClient(orthanc_root_url)
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20 for i in range(0, repeat):
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21 o.upload_folder(folder, ignore_errors=True)
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22
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23 def worker_anonymize_study(orthanc_root_url: str, study_id: str, repeat: int, worker_id: int):
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24 o = OrthancApiClient(orthanc_root_url)
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25
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26 for i in range(0, repeat):
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27 o.studies.anonymize(orthanc_id=study_id, delete_original=False)
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28
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597
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29 def count_changes(changes, type: ChangeType):
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30 return len([c.change_type for c in changes if c.change_type==type])
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31
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32 def worker_upload_delete_study_part(orthanc_root_url: str, folder: str, repeat: int, workers_count: int, worker_id: int):
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33 o = OrthancApiClient(orthanc_root_url)
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34
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35 all_files = glob.glob(os.path.join(folder, '*.dcm'))
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36
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37 for i in range(0, repeat):
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38 instances_ids = []
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39
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40 for i in range(0, len(all_files)):
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598
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41 if i % workers_count == worker_id: # each thread takes a part
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42 instances_ids.extend(o.upload_file(all_files[i]))
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43
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44 for instance_id in instances_ids:
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45 o.instances.delete(orthanc_id=instance_id, ignore_errors=True)
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46
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47
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598
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48 def worker_upload_delete_test_dicoms(orthanc_root_url: str, files_count: int, worker_id: int):
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49 o = OrthancApiClient(orthanc_root_url)
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50
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51 instances_ids = []
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52 counter = 0
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53
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54 for i in range(0, files_count):
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55 counter += 1
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56 dicom_file = OrthancHelpers.generate_test_dicom_file(width=4, height=4,
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57 tags = {
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58 "PatientID" : f"{worker_id}",
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59 "StudyInstanceUID" : f"{worker_id}",
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60 "SeriesInstanceUID" : f"{worker_id}.{counter%10}"
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61 })
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62 instances_ids.extend(o.upload(dicom_file))
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63
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64 study_id = o.instances.get_parent_study_id(instances_ids[0])
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65 o.studies.delete(orthanc_id=study_id)
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66
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67
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592
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68 class TestConcurrency(OrthancTestCase):
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69
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70 @classmethod
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71 def terminate(cls):
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72
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73 if Helpers.is_docker():
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74 subprocess.run(["docker", "rm", "-f", "pg-server"])
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75 else:
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76 cls.pg_service_process.terminate()
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77
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78
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79 @classmethod
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80 def prepare(cls):
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81 test_name = "Concurrency"
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82 cls._storage_name = "concurrency"
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83
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84 print(f'-------------- preparing {test_name} tests')
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85
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86 cls.clear_storage(storage_name=cls._storage_name)
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87
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88 pg_hostname = "localhost"
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89 if Helpers.is_docker():
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90 pg_hostname = "pg-server"
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91 cls.create_docker_network("concurrency")
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92
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93 config = {
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94 "PostgreSQL" : {
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95 "EnableStorage": False,
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96 "EnableIndex": True,
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97 "Host": pg_hostname,
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98 "Port": 5432,
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99 "Database": "postgres",
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100 "Username": "postgres",
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101 "Password": "postgres",
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102 "IndexConnectionsCount": 10,
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103 "MaximumConnectionRetries" : 2000,
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104 "ConnectionRetryInterval" : 5,
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105 "TransactionMode": "READ COMMITTED",
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106 #"TransactionMode": "SERIALIZABLE",
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107 "EnableVerboseLogs": True
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108 },
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109 "AuthenticationEnabled": False,
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110 "OverwriteInstances": True,
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111 "JobsEngineThreadsCount" : {
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112 "ResourceModification": 8
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113 },
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114 }
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115
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116 config_path = cls.generate_configuration(
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117 config_name=f"{test_name}",
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118 storage_name=cls._storage_name,
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119 config=config,
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120 plugins=Helpers.plugins
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121 )
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122
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123 # launch the docker PG server
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124 print('--------------- launching PostgreSQL server ------------------')
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125
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126 cls.pg_service_process = subprocess.Popen([
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127 "docker", "run", "--rm",
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128 "-p", "5432:5432",
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129 "--network", "concurrency",
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130 "--name", "pg-server",
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131 "--env", "POSTGRES_HOST_AUTH_METHOD=trust",
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132 "postgres:15"])
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133 time.sleep(5)
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134
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135 if Helpers.break_before_preparation:
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136 print(f"++++ It is now time to start your Orthanc under tests with configuration file '{config_path}' +++++")
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137 input("Press Enter to continue")
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138 else:
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139 cls.launch_orthanc_under_tests(
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140 config_name=f"{test_name}",
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141 storage_name=cls._storage_name,
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142 config=config,
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143 plugins=Helpers.plugins,
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144 docker_network="concurrency"
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145 )
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146
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147 cls.o = OrthancApiClient(cls.o._root_url)
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148 cls.o.wait_started()
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149 cls.o.delete_all_content()
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150
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151 def check_is_empty(self):
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152 self.assertEqual(0, len(self.o.studies.get_all_ids()))
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153 self.assertEqual(0, len(self.o.series.get_all_ids()))
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154 self.assertEqual(0, len(self.o.instances.get_all_ids()))
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155
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156 stats = self.o.get_json("/statistics")
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157 self.assertEqual(0, stats.get("CountPatients"))
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158 self.assertEqual(0, stats.get("CountStudies"))
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159 self.assertEqual(0, stats.get("CountSeries"))
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160 self.assertEqual(0, stats.get("CountInstances"))
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161 self.assertEqual(0, int(stats.get("TotalDiskSize")))
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162 # time.sleep(10000)
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163 self.assertTrue(self.is_storage_empty(self._storage_name))
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164
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165 # all changes shall have been deleted as well
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166 changes, last_change, done = self.o.get_changes(since=0, limit=100000)
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167 self.assertTrue(done)
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168 self.assertEqual(0, len(changes))
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169
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592
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170
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171 def execute_workers(self, worker_func, worker_args, workers_count):
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172 workers = []
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173 for i in range(0, workers_count):
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174 t = threading.Thread(target=worker_func, args=worker_args + (i, ))
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175 workers.append(t)
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176 t.start()
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177
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178 for t in workers:
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179 t.join()
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180
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181 def test_concurrent_uploads_same_study(self):
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182 self.o.delete_all_content()
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183 self.clear_storage(storage_name=self._storage_name)
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184
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185 start_time = time.time()
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186 workers_count = 20
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187 repeat_count = 1
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188
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189 # massively reupload the same study multiple times with OverwriteInstances set to true
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190 # Make sure the studies, series and instances are created only once
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191 self.execute_workers(
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192 worker_func=worker_upload_folder,
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193 worker_args=(self.o._root_url, here / "../../Database/Knee", repeat_count,),
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194 workers_count=workers_count)
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195
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196 elapsed = time.time() - start_time
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197 print(f"TIMING test_concurrent_uploads_same_study with {workers_count} workers and {repeat_count}x repeat: {elapsed:.3f} s")
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198
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199 self.assertTrue(self.o.is_alive())
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200
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201 self.assertEqual(1, len(self.o.studies.get_all_ids()))
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202 self.assertEqual(2, len(self.o.series.get_all_ids()))
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203 self.assertEqual(50, len(self.o.instances.get_all_ids()))
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204
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205 stats = self.o.get_json("/statistics")
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206 self.assertEqual(1, stats.get("CountPatients"))
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207 self.assertEqual(1, stats.get("CountStudies"))
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208 self.assertEqual(2, stats.get("CountSeries"))
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209 self.assertEqual(50, stats.get("CountInstances"))
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210 self.assertEqual(4118738, int(stats.get("TotalDiskSize")))
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211
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212 self.o.instances.delete(orthanc_ids=self.o.instances.get_all_ids())
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213
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597
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214 self.check_is_empty()
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592
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215
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216 def test_concurrent_anonymize_same_study(self):
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217 self.o.delete_all_content()
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218 self.clear_storage(storage_name=self._storage_name)
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219
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220 self.o.upload_folder(here / "../../Database/Knee")
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221 study_id = self.o.studies.get_all_ids()[0]
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222
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223 start_time = time.time()
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224 workers_count = 4
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225 repeat_count = 10
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226
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227 # massively anonymize the same study. This generates new studies and is a
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228 # good way to simulate ingestion of new studies
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229 self.execute_workers(
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230 worker_func=worker_anonymize_study,
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231 worker_args=(self.o._root_url, study_id, repeat_count,),
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232 workers_count=workers_count)
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233
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234 elapsed = time.time() - start_time
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593
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235 print(f"TIMING test_concurrent_anonymize_same_study with {workers_count} workers and {repeat_count}x repeat: {elapsed:.3f} s")
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592
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236
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237 self.assertTrue(self.o.is_alive())
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238
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239 self.assertEqual(1 + workers_count * repeat_count, len(self.o.studies.get_all_ids()))
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240 self.assertEqual(2 * (1 + workers_count * repeat_count), len(self.o.series.get_all_ids()))
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241 self.assertEqual(50 * (1 + workers_count * repeat_count), len(self.o.instances.get_all_ids()))
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242
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243 stats = self.o.get_json("/statistics")
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244 self.assertEqual(1 + workers_count * repeat_count, stats.get("CountPatients"))
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245 self.assertEqual(1 + workers_count * repeat_count, stats.get("CountStudies"))
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246 self.assertEqual(2 * (1 + workers_count * repeat_count), stats.get("CountSeries"))
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247 self.assertEqual(50 * (1 + workers_count * repeat_count), stats.get("CountInstances"))
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248 changes, last_change, done = self.o.get_changes(since=0, limit=100000)
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249 self.assertTrue(done)
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250
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251 self.assertEqual(1 + workers_count * repeat_count, count_changes(changes, ChangeType.NEW_PATIENT))
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252 self.assertEqual(1 + workers_count * repeat_count, count_changes(changes, ChangeType.NEW_STUDY))
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253 self.assertEqual(2 * (1 + workers_count * repeat_count), count_changes(changes, ChangeType.NEW_SERIES))
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254 self.assertEqual(50 * (1 + workers_count * repeat_count), count_changes(changes, ChangeType.NEW_INSTANCE))
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255
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593
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256 start_time = time.time()
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257
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258 self.o.instances.delete(orthanc_ids=self.o.instances.get_all_ids())
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259
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260 elapsed = time.time() - start_time
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261 print(f"TIMING test_concurrent_anonymize_same_study deletion took: {elapsed:.3f} s")
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262
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263 self.check_is_empty()
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264
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265
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266 def test_upload_delete_same_study_from_multiple_threads(self):
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267 self.o.delete_all_content()
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268 self.clear_storage(storage_name=self._storage_name)
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269
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270 start_time = time.time()
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596
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271 overall_repeat = 10
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272
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273 for i in range(0, overall_repeat):
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274 workers_count = 5
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596
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275 repeat_count = 3
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594
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276
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277 # massively upload and delete the same study. Each worker is writing a part of the instances and deleting them.
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278 # We are trying to have multiple workers deleting the last instance of a study at the same time.
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279 self.execute_workers(
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280 worker_func=worker_upload_delete_study_part,
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281 worker_args=(self.o._root_url, here / "../../Database/Knee/T1", repeat_count, workers_count, ),
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282 workers_count=workers_count)
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592
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283
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597
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284 self.check_is_empty()
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592
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285
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286 elapsed = time.time() - start_time
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596
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287 print(f"TIMING test_upload_delete_same_study_from_multiple_threads with {workers_count} workers and {repeat_count}x repeat ({overall_repeat}x): {elapsed:.3f} s")
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592
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288
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289
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598
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290 def test_upload_multiple_studies_from_multiple_threads(self):
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291 self.o.delete_all_content()
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292 self.clear_storage(storage_name=self._storage_name)
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293
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294 start_time = time.time()
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295 overall_repeat = 3
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296
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297 for i in range(0, overall_repeat):
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298 files_count = 25
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299 workers_count = 10
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300
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301 # massively upload and delete all studies from the test detabase. Each worker is writing all instances from a folder and then deletes them.
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302 # This test is only measuring performances.
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303 self.execute_workers(
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304 worker_func=worker_upload_delete_test_dicoms,
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305 worker_args=(self.o._root_url, files_count, ),
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306 workers_count=workers_count)
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307
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308 self.check_is_empty()
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309
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310 elapsed = time.time() - start_time
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311 print(f"TIMING test_upload_multiple_studies_from_multiple_threads with {workers_count} workers and {files_count} files and repeat {overall_repeat}x: {elapsed:.3f} s")
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312
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592
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313 # transfers + dicomweb |
