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added links to uclouvain
author Sebastien Jodogne <s.jodogne@gmail.com>
date Wed, 20 Dec 2023 08:12:21 +0100
parents 6b959b4823aa
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1 .. _scalability:
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2
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3 Scalability of Orthanc
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4 ======================
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5
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6 .. contents::
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7
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8 Overview
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9 --------
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11 One of the most common question about Orthanc is: *"How many DICOM
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12 instances can be stored by Orthanc?"*
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14 The source code of Orthanc imposes no such hard limit by itself.
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15
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16 At the time of writing, we know that Orthanc is being used in
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17 production in hospitals with more than 15TB of data, 125,000 studies
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18 and around 50 millions of instances (please `get in touch with us
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19 <https://www.orthanc-server.com/static.php?page=contact>`__ if you can
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20 share other testimonials). Other users have even reported more than
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21 28TB of data. Here are links to some testimonials that were published
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22 on the `Orthanc Users discussion forum
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23 <https://discourse.orthanc-server.org>`__ discussion
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24 group: `1
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25 <https://groups.google.com/d/msg/orthanc-users/-L0D1c2y6rw/KmWnwEijAgAJ>`__,
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26 `2
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27 <https://groups.google.com/d/msg/orthanc-users/-L0D1c2y6rw/nLXxtYzuCQAJ>`__,
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28 `3
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29 <https://groups.google.com/d/msg/orthanc-users/s5-XlgA2BEY/ZpYagqBwAAAJ>`__,
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30 `4
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31 <https://groups.google.com/d/msg/orthanc-users/A4hPaJo439s/NwR6zk9FCgAJ>`__,
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32 `5
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33 <https://groups.google.com/d/msg/orthanc-users/Z5cLwbVgJc0/SxVzxF7ABgAJ>`__,
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34 `6
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35 <https://groups.google.com/d/msg/orthanc-users/6tGNOqlUk-Q/vppkAYnFAQAJ>`__...
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36
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37 The stress is actually put on the underlying database engine, and on
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38 the storage area (check out :ref:`orthanc-storage`). As explained in
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39 the :ref:`troubleshooting section <troubleshooting>`, the built-in
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40 SQLite database engine should be replaced by an enterprise-ready
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41 database engine once Orthanc must store several hundreds of thousands
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42 of DICOM instances (check out the :ref:`postgresql` and
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43 :ref:`mysql`). It is also true that the performance of Orthanc in the
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44 presence of large databases has continuously improved over time,
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45 especially when it comes to the speed of :ref:`DICOM C-FIND
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46 <dicom-find>`.
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49 .. _scalability-setup:
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50
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51 Recommended setup for best performance
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52 --------------------------------------
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54 Here is a generic setup that should provide best performance in the
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55 presence of large databases:
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56
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57 * Make sure to use the latest release of Orthanc (1.12.2 at the time of
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58 writing) running on a GNU/Linux distribution.
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59
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60 * We suggest to use the latest release of the :ref:`PostgreSQL plugin
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61 <postgresql>` to store the database index (5.0 at the time of
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62 writing). Make sure that ``EnableIndex`` is set to ``true``.
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63
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64 * Make sure that :ref:`run-time debug assertions <troubleshooting>`
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65 are turned off. A warning will show in the logs if this is not the
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66 case. Note that all `pre-compiled binaries
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67 <https://orthanc.uclouvain.be/downloads/index.html>`__ provided by
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68 the Orthanc project are correctly configured in that respect, except
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69 if they are explicitly tagged as "debug".
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71 * We suggest to use the default filesystem storage area. Of course,
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72 make sure that the filesystem is properly backed up, and that
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73 technologies such as RAID are enabled. Make sure that the option
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74 ``EnableStorage`` of the PostgreSQL plugins is set to ``false``.
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75
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76 * Obviously, the PostgreSQL database should be stored on a high-speed
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77 drive (SSD). This is less important for the storage area.
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79 * It may be useful to store the PostgreSQL database on another drive
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80 than the storage area. This should improve the use of the available
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81 bandwidth to the disks.
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82
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83 * If your Orthanc instance is performing a lot of IO requests in parallel
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84 e.g because many clients are reading/writing DICOM files at the same
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85 time, you should consider using an :ref:`object storage <object-storage>`
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86 plugin to store your files.
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88 * The :ref:`Orthanc configuration file <configuration>` should have
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89 the following values for performance-related options (but make sure
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90 to understand their implications):
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91
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92 * ``StorageCompression = false``
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93 * ``LimitFindResults = 100``
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94 * ``LimitFindInstances = 100``
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95 * ``KeepAlive = true``
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96 * ``TcpNoDelay = true``
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97 * ``StorageAccessOnFind = Never``
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98 * Consider adding ``SaveJobs = false``
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100 * Since Orthanc 1.9.2 and PostgreSQL plugins 4.0: By default, the
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101 PostgreSQL index plugin uses 1 single connection to the PostgreSQL
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102 database. You can have multiple connections by setting the
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103 ``IndexConnectionsCount`` to a higher value (for instance ``5``) in
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104 the ``PostgreSQL`` section of the configuration file. This will
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105 improve concurrency. Check out :ref:`the explanation below <multiple-writers>`.
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106
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107 * Since Orthanc 1.9.2 and PostgreSQL plugins 4.0: If you have an
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108 hospital-wide VNA deployment, you could consider to deploy multiple
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109 Orthanc servers sharing the same PostgreSQL database. A typical
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110 scenario is having one "writer" Orthanc server that handles the
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111 ingesting of DICOM instances, and multiple "reader" Orthanc servers
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112 with features such as DICOMweb or viewers.
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114 * From Orthanc 1.11.0: you have the ability to add
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115 more :ref:`main DICOM tags <main-dicom-tags>` in the Orthanc Index
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116 to speed up C-Find, ``tools/find``, DICOMWeb QIDO-RS, WADO-RS and
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117 especially WADO-RS Retrieve Metadata.
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118
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119 * Make sure to carefully :ref:`read the logs <log>` in ``--verbose``
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120 mode, especially at the startup of Orthanc. The logs may contain
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121 very important information regarding performance.
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123 * Make sure to read guides about the `tuning of PostgreSQL
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124 <https://wiki.postgresql.org/wiki/Performance_Optimization>`__.
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126 * Make sure to enable the `Autovacuum Daemon
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127 <https://www.postgresql.org/docs/current/routine-vacuuming.html>`__
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128 of PostgreSQL, or to periodically run the ``VACUUM`` SQL command on
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129 the PostgreSQL database in order to `reclaim the storage space
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130 <https://www.postgresql.org/docs/current/sql-vacuum.html>`__ that is
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131 occupied by rows that have been deleted from the database (e.g. in a
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132 cron job).
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133
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134 * You might also be interested in checking the options related to
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135 :ref:`security <security>`.
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136
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137 * Consider using filesystems that are known to achieve high
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138 performance, such as `XFS <https://en.wikipedia.org/wiki/XFS>`__ or
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139 `Btrfs <https://en.wikipedia.org/wiki/Btrfs>`__ on GNU/Linux
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140 distributions.
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141
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142 * If you need to grow the storage area as more space becomes needed,
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143 you can consider the following solutions:
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144
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145 - Move the storage area to another disk partition, and update the
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146 ``StorageDirectory`` :ref:`configuration option <configuration>`
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147 accordingly.
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148 - :ref:`Replicate <replication>` your current instance of Orthanc
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149 onto another instance of Orthanc with a larger storage area.
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150 - On GNU/Linux distributions, check out `LVM (Logical Volume Manager)
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151 <https://en.wikipedia.org/wiki/Logical_Volume_Manager_(Linux)>`__.
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152 - On Microsoft Windows, check out the so-called "`Storage Spaces
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153 <https://docs.microsoft.com/en-us/windows-server/storage/storage-spaces/overview>`__".
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154 - Another approach is to use `MinIO <https://docs.min.io/>`__ in
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155 distributed mode in conjunction with the :ref:`AWS S3 plugin
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156 <minio>` for Orthanc.
318
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157
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158 * If using the :ref:`DICOMweb server plugin <dicomweb-server-config>`,
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159 consider setting configuration option ``StudiesMetadata`` to
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160 ``MainDicomTags``.
384
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161
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162 * If using PostgreSQL as a managed cloud service by Microsoft Azure,
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163 make sure to reduce the verbosity of the logs. If logging is not
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164 minimal, Osimis has observed an impact on performance.
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165
384
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166
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167 .. _scalability-memory:
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168
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169 Controlling memory usage
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170 ------------------------
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171
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172 The absence of memory leaks in Orthanc is verified thanks to `valgrind
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173 <https://valgrind.org/>`__.
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174
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175 On GNU/Linux systems, you might however `observe a large memory
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176 consumption
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177 <https://groups.google.com/d/msg/orthanc-users/qWqxpvCPv8g/47wnYyhOCAAJ>`__
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178 in the "resident set size" (VmRSS) of the application, notably if you
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179 upload multiple large DICOM files using the REST API.
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180
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181 This large memory consumption comes from the fact that the embedded
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182 HTTP server is heavily multi-threaded, and that many so-called `memory
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183 arenas <https://sourceware.org/glibc/wiki/MallocInternals>`__ are
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184 created by the glibc standard library (up to one per thread). As a
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185 consequence, if each one of the 50 threads in the HTTP server of
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186 Orthanc (default value of the ``HttpThreadsCount`` option) allocates
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187 at some point, say, 50MB, the total memory usage reported as "VmRSS"
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188 can grow up to 50 threads x 50MB = 2.5GB, even if the Orthanc threads
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189 properly free all the buffers.
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190
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191 .. highlight:: bash
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192
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193 A possible solution to reducing this memory usage is to ask glibc to
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194 limit the number of "memory arenas" that are used by the Orthanc
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195 process. On GNU/Linux, this can be controlled by setting the
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196 environment variable ``MALLOC_ARENA_MAX``. For instance, the following
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197 bash command-line would use one single arena that is shared by all the
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198 threads in Orthanc::
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199
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200 $ MALLOC_ARENA_MAX=1 ./Orthanc
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201
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202 Obviously, this restrictive setting will use minimal memory, but will
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203 result in contention among the threads. A good compromise might be to
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204 use 5 arenas::
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205
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206 $ MALLOC_ARENA_MAX=5 ./Orthanc
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207
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208 Memory allocation on GNU/Linux is a complex topic. There are other
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209 options available as environment variables that could also reduce
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210 memory consumption (for instance, ``MALLOC_MMAP_THRESHOLD_`` would
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211 bypass arenas for large memory blocks such as DICOM files). Check out
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212 the `manpage <http://man7.org/linux/man-pages/man3/mallopt.3.html>`__
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213 of ``mallopt()`` for more information.
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214
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215 **Status:**
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216
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217 * Since **Orthanc 1.8.2**, the global configuration ``MallocArenaMax``
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218 automatically sets ``MALLOC_MMAP_THRESHOLD_`` (defaults to ``5``)
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219 during the startup of Orthanc.
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220
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221 * The ``jodogne/orthanc`` and ``jodogne/orthanc-plugins`` Docker
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222 images automatically set ``MALLOC_ARENA_MAX`` to ``5`` **since
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223 release 1.6.1** (cf. `changeset
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224 <https://github.com/jodogne/OrthancDocker/commit/bd7e9f4665ce8dd6892f82a148cabe8ebcf1c7d9>`__).
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225
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226 * The ``osimis/orthanc`` images automatically set
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227 ``MALLOC_ARENA_MAX`` to ``5`` **since release 20.12.2**.
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228
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229
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230 .. _scalability-limitations:
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231
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232 Known limitations
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233 -----------------
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234
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235 Exclusive access to the DB in Orthanc <= 1.9.1
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236 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
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237
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238 Orthanc was originally designed as a mini-DICOM server in 1-to-1
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239 relation with a SQLite database. Until **Orthanc 1.9.1**, because of
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240 this original design, the internal code accessing the DB was affected
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241 by a strong limitation: Inside a single Orthanc process, there was no
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242 concurrent access to the DB.
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243
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244 One solution to avoid this limitation was to have multiple Orthanc
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245 accessing the same DB (works only for MySQL and PostgreSQL) as
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246 presented in this `sample
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247 <https://github.com/orthanc-server/orthanc-setup-samples/tree/master/docker/multiple-orthancs-on-same-db/>`__.
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248 However, this solution was only robust if there was **one single
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249 "writer" Orthanc server** (i.e. only one Orthanc was modifying the
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250 database). Indeed, the core of Orthanc <= 1.9.1 did not support the
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251 replay of database transactions, which is necessary to deal with
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252 conflicts between several instances of Orthanc that would
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253 simultaneously write to the database.
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254
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255 Concretely, in Orthanc <= 1.9.1, when connecting multiple Orthanc to a
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256 single database by setting ``Lock`` to ``false``, there should only be
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257 one instance of Orthanc acting as a writer and all the other instances
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258 of Orthanc acting as readers only. Be careful to set the option
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259 ``SaveJobs`` to ``false`` in the configuration file of all the
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260 instances of Orthanc acting as readers (otherwise the readers would
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261 also modify the database).
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262
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263 Some issues reported in our bug tracker are related this limitation:
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264 `issue 83 <https://orthanc.uclouvain.be/bugs/show_bug.cgi?id=83>`__,
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265 `issue 121 <https://orthanc.uclouvain.be/bugs/show_bug.cgi?id=121>`__,
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266 `issue 151 <https://orthanc.uclouvain.be/bugs/show_bug.cgi?id=151>`__.
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267
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268 This limitation has disappeared with Orthanc 1.9.2 and
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269 PostgreSQL/MySQL plugins 4.0, were the database engine was fully
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270 rewritten.
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271
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272
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273 .. _multiple-writers:
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274
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275 Concurrent accesses to the DB in Orthanc >= 1.9.2
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276 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
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277
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278 In **Orthanc 1.9.2 and PostgreSQL/MySQL plugins 4.0**, the database
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279 engine of Orthanc was rewritten from scratch to allow multiple
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280 writers/readers to share the same database. This new feature
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281 necessitated a full refactoring of the database engine, so as to
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282 replay transactions in the case of collisions between concurrent
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283 transactions to the database.
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284
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285 Furthermore, one Orthanc server can also manage several connections to
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286 PostgreSQL or MySQL, in order to improve performance by adding
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287 concurrency. Read-only database transactions are also distinguished
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288 from read-write transactions in order for the database engine to
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289 further optimize the patterns of access.
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290
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291 Summarizing, the **multiple readers/writers** is now possible. Here is
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292 a drawing representing a possible deployment with 4 Orthanc servers,
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293 all sharing the same DICOM images, with some servers handling multiple
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294 connections to a PostgreSQL database for higher throughput:
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295
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296 .. image:: ../images/2021-04-22-MultipleWriters.png
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297 :align: center
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298 :width: 500px
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299
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300 Care must be taken to the following aspects:
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301
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302 * Orthanc 1.9.2 must be combined with a database plugin that supports
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303 multiple writers. This is the case of the PostgreSQL and MySQL
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304 plugins with version >= 4.0. The built-in SQLite database **does
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305 not** support multiple writers.
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306
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307 * Concurrent access can result in so-called `non-serializable
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308 transactions
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309 <https://en.wikipedia.org/wiki/Isolation_(database_systems)#Serializable>`__
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310 if two separate database transactions modify the database at the
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311 same time (cf. ``ErrorCode_DatabaseCannotSerialize`` in the source
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312 code of Orthanc). Orthanc will **automatically replay such
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313 transactions** a certain number of times (waiting 100ms more between
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314 each retry), until the transactions succeed. The plugins provide an
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315 option to control the maximum number of retries. If the maximum
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316 number of retries is exceeded, the ``503 Service Unavailable`` HTTP
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317 error is raised (server overloaded because of unsuccessful retries
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318 of concurrent transactions).
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319
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320 * If a higher-level application **modifies metadata and/or
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321 attachments** in the presence of multiple writers, Orthanc provides
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322 a :ref:`revision mechanism <revisions>` to prevent concurrent
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323 updates.
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324
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325 * Thanks to this support of concurrent accesses, it is possible to put
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326 a **load balancer** on the top of the REST API of Orthanc. All the
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327 DICOM resources (patients, studies, series and instances) are indeed
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328 shared by all the instances of Orthanc connected to the same
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329 underlying database. As an application, this might be of great help
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330 if multiple viewers must connect to Orthanc. In `Kubernetes
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331 <https://kubernetes.io/>`__, concurrent accesses also make it
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332 possible to manage a set of replicas of Orthanc (e.g. as `deployment
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333 <https://kubernetes.io/docs/concepts/workloads/controllers/deployment/>`__).
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334
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335 There are however some caveats if using a load balancer or
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336 Kubernetes replicas, notably:
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337
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338 - Each Orthanc instance maintains its own list of jobs. Therefore,
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339 the ``/jobs`` route will return only the jobs of the responding
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340 Orthanc.
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341
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342 - Similarly, each Orthanc instance maintains its own :ref:`status
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343 for the resources it has received <stable-resources>`. Thus, the
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344 ``IsStable`` information is local to each Orthanc instance.
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345
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346 - The ``/modalities`` or the ``/peers`` are also private to each
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347 instance of Orthanc in the cluster, as soon as the respective
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348 options ``DicomModalitiesInDatabase`` and
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349 ``OrthancPeersInDatabase`` are set to ``true``.
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350
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351 If you need to use such primitives in your application, you have
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352 three possibilities: (1) Introduce a distinguished Orthanc server
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353 that is responsible to take care of all the jobs (including
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354 modalities and peers) and/or to receive all the DICOM instances, (2)
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355 create an :ref:`Orthanc plugin <plugins>` (e.g. using :ref:`Python
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356 <python-plugin>` or :ref:`Java <java-plugin>`) that queries all the
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357 Orthanc in the cluster and that aggregates all of their answers,
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358 or (3) do the same using a higher-level framework (such as Node.js).
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359
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360
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361 Latency
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362 ^^^^^^^
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363
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364 For some queries to the database, Orthanc performs several small SQL
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365 requests. For instance, a request to a route like ``/studies/{id}``
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366 can trigger 6 SQL queries. Given these round-trips between Orthanc and
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367 the DB server, it's important for the **network latency to be as small
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368 as possible**. For instance, if your latency is 20ms, a single request
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369 to ``/studies/{id}`` might take 120ms. Typically, a latency of 1-4 ms
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370 is expected to have correct performances.
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371
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372 As a consequence, if deploying Orthanc in a cloud infrastructure, make
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373 sure that the DB server and Orthanc VMs are located in the **same
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374 datacenter**. Note that most of the time-consuming queries have
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375 already been optimized, and that future versions of Orthanc SDK might
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376 aggregate even more SQL requests.
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377
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378 Starting with Orthanc 1.9.2, and PostgreSQL/MySQL index plugins 4.0,
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379 Orthanc can also be configured to handle **multiple connections to the
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380 database server** by setting the ``IndexConnectionsCount`` to a value
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381 greater than ``1``. This allows concurrent accesses to the database,
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382 which avoids to sequentially wait for a database transaction to be
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383 concluded before starting another one. Having multiple connections
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384 makes the latency problem much less important.
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385
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386
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387 Slow deletions
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388 ^^^^^^^^^^^^^^
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389
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390 Deleting large studies can take much time, because removing a large
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391 number of files from a filesystem can be an expensive operation (which
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392 might sound counter-intuitive). This is especially true with HDD
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393 drives, that can be much slower than SSD (`an user has reported
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394 <https://groups.google.com/g/orthanc-users/c/1lga0oFCHN4/m/jF1inrc4AgAJ>`__
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395 a 20 times speedup by switching from HDD to SSD).
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396
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397 If switching from HDD to SDD is not applicable, you may also use
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398 the :ref:`Delayed Deletion plugin <delayed-deletion-plugin>` .
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399 The plugin would maintains a queue of files to be removed. The actual
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400 deletion from the filesystem is done asynchronously in a
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401 separate thread.