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Chen, Junjie
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Reviewed-by: Hasko, Vladimir <vladimir.hasko@t-systems.com> Co-authored-by: Chen, Junjie <chenjunjie@huawei.com> Co-committed-by: Chen, Junjie <chenjunjie@huawei.com>
86 lines
6.8 KiB
HTML
86 lines
6.8 KiB
HTML
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<h1 class="topictitle1">Redis Cluster</h1>
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<div id="body1600250976541"><p id="CacheProxy__p7253192101916">This section describes Redis Cluster DCS Redis 4.0 and 5.0 instances.</p>
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<div class="section" id="CacheProxy__section880163191618"><h4 class="sectiontitle">Redis Cluster DCS Redis 4.0 and 5.0 Instances</h4><p id="CacheProxy__p1977021012338">The Redis Cluster instance type provided by DCS is compatible with the <a href="https://redis.io/topics/cluster-spec" target="_blank" rel="noopener noreferrer">native Redis Cluster</a>, which uses smart clients and a distributed architecture to perform sharding.</p>
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<p id="CacheProxy__p164954315218"><a href="#CacheProxy__table3552324111">Table 1</a> lists the shard specification for different instance specifications.</p>
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<p id="CacheProxy__p17223016111"><strong id="CacheProxy__b94915132075659">Specification per shard=Instance specification/Number of shards</strong>. For example, if a 48 GB instance has 6 shards, the specification of each shard is 48 GB/6 = 8 GB.</p>
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<div class="tablenoborder"><a name="CacheProxy__table3552324111"></a><a name="table3552324111"></a><table cellpadding="4" cellspacing="0" summary="" id="CacheProxy__table3552324111" frame="border" border="1" rules="all"><caption><b>Table 1 </b>Specifications of Redis Cluster DCS instances</caption><thead align="left"><tr id="CacheProxy__row65521623113"><th align="left" class="cellrowborder" valign="top" width="44.12%" id="mcps1.3.2.5.2.3.1.1"><p id="CacheProxy__p1955210211118">Total Memory</p>
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</th>
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<th align="left" class="cellrowborder" valign="top" width="55.879999999999995%" id="mcps1.3.2.5.2.3.1.2"><p id="CacheProxy__p04843421456">Shards</p>
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</th>
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</tr>
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</thead>
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<tbody><tr id="CacheProxy__row155314218115"><td class="cellrowborder" valign="top" width="44.12%" headers="mcps1.3.2.5.2.3.1.1 "><p id="CacheProxy__p491514405611">4 GB/8 GB/16 GB/24 GB/32 GB</p>
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</td>
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<td class="cellrowborder" valign="top" width="55.879999999999995%" headers="mcps1.3.2.5.2.3.1.2 "><p id="CacheProxy__p207903579620">3</p>
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</td>
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</tr>
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<tr id="CacheProxy__row1731117227614"><td class="cellrowborder" valign="top" width="44.12%" headers="mcps1.3.2.5.2.3.1.1 "><p id="CacheProxy__p99166401567">48 GB</p>
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</td>
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<td class="cellrowborder" valign="top" width="55.879999999999995%" headers="mcps1.3.2.5.2.3.1.2 "><p id="CacheProxy__p1779095710616">6</p>
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</td>
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</tr>
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<tr id="CacheProxy__row113126221669"><td class="cellrowborder" valign="top" width="44.12%" headers="mcps1.3.2.5.2.3.1.1 "><p id="CacheProxy__p891617401862">64 GB</p>
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</td>
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<td class="cellrowborder" valign="top" width="55.879999999999995%" headers="mcps1.3.2.5.2.3.1.2 "><p id="CacheProxy__p97906571561">8</p>
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</td>
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</tr>
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<tr id="CacheProxy__row10313162217619"><td class="cellrowborder" valign="top" width="44.12%" headers="mcps1.3.2.5.2.3.1.1 "><p id="CacheProxy__p19161140362">96 GB</p>
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</td>
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<td class="cellrowborder" valign="top" width="55.879999999999995%" headers="mcps1.3.2.5.2.3.1.2 "><p id="CacheProxy__p879011574611">12</p>
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</td>
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</tr>
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<tr id="CacheProxy__row93136221568"><td class="cellrowborder" valign="top" width="44.12%" headers="mcps1.3.2.5.2.3.1.1 "><p id="CacheProxy__p15916164015619">128 GB</p>
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</td>
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<td class="cellrowborder" valign="top" width="55.879999999999995%" headers="mcps1.3.2.5.2.3.1.2 "><p id="CacheProxy__p1679065712610">16</p>
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</td>
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</tr>
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<tr id="CacheProxy__row123147221965"><td class="cellrowborder" valign="top" width="44.12%" headers="mcps1.3.2.5.2.3.1.1 "><p id="CacheProxy__p1591613409619">192 GB</p>
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</td>
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<td class="cellrowborder" valign="top" width="55.879999999999995%" headers="mcps1.3.2.5.2.3.1.2 "><p id="CacheProxy__p137910577616">24</p>
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</td>
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</tr>
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<tr id="CacheProxy__row1297218281269"><td class="cellrowborder" valign="top" width="44.12%" headers="mcps1.3.2.5.2.3.1.1 "><p id="CacheProxy__p4916140966">256 GB</p>
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</td>
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<td class="cellrowborder" valign="top" width="55.879999999999995%" headers="mcps1.3.2.5.2.3.1.2 "><p id="CacheProxy__p87911957860">32</p>
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</td>
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</tr>
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<tr id="CacheProxy__row14566154853519"><td class="cellrowborder" valign="top" width="44.12%" headers="mcps1.3.2.5.2.3.1.1 "><p id="CacheProxy__p356774883515">384 GB</p>
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</td>
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<td class="cellrowborder" valign="top" width="55.879999999999995%" headers="mcps1.3.2.5.2.3.1.2 "><p id="CacheProxy__p10567548133513">48</p>
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</td>
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</tr>
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<tr id="CacheProxy__row8567124814359"><td class="cellrowborder" valign="top" width="44.12%" headers="mcps1.3.2.5.2.3.1.1 "><p id="CacheProxy__p14311185913513">512 GB</p>
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</td>
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<td class="cellrowborder" valign="top" width="55.879999999999995%" headers="mcps1.3.2.5.2.3.1.2 "><p id="CacheProxy__p20567184883518">64</p>
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</td>
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</tr>
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<tr id="CacheProxy__row7567114814356"><td class="cellrowborder" valign="top" width="44.12%" headers="mcps1.3.2.5.2.3.1.1 "><p id="CacheProxy__p967654163618">768 GB</p>
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</td>
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<td class="cellrowborder" valign="top" width="55.879999999999995%" headers="mcps1.3.2.5.2.3.1.2 "><p id="CacheProxy__p13568194813354">96</p>
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</td>
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</tr>
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<tr id="CacheProxy__row1656844810350"><td class="cellrowborder" valign="top" width="44.12%" headers="mcps1.3.2.5.2.3.1.1 "><p id="CacheProxy__p209424813617">1024 GB</p>
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</td>
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<td class="cellrowborder" valign="top" width="55.879999999999995%" headers="mcps1.3.2.5.2.3.1.2 "><p id="CacheProxy__p155682483350">128</p>
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</td>
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</tr>
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</tbody>
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</table>
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</div>
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<ul id="CacheProxy__ul123731121185515"><li id="CacheProxy__li3970143612556">Distributed architecture<p id="CacheProxy__p6111153985512"><a name="CacheProxy__li3970143612556"></a><a name="li3970143612556"></a>Any node in a Redis Cluster can receive requests. Received requests are then redirected to the right node for processing. Each node consists of a subset of one master and one (by default) or multiple replicas. The master or replica roles are determined through an election algorithm.</p>
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<div class="fignone" id="CacheProxy__fig736144082814"><span class="figcap"><b>Figure 1 </b>Distributed architecture of Redis Cluster</span><br><span><img id="CacheProxy__image0855192718314" src="en-us_image_0277578727.png"></span></div>
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</li><li id="CacheProxy__li1693714855516">Presharding<p id="CacheProxy__p2019185113552"><a name="CacheProxy__li1693714855516"></a><a name="li1693714855516"></a>There are 16,384 hash slots in each Redis Cluster. The mapping between hash slots and Redis nodes is stored in Redis Servers. To compute what is the hash slot of a given key, simply take the CRC16 of the key modulo 16384. Example command output</p>
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<div class="fignone" id="CacheProxy__fig114922024115011"><span class="figcap"><b>Figure 2 </b>Redis Cluster presharding</span><br><span><img id="CacheProxy__image1087382672319" src="en-us_image_0000001280621500.png"></span></div>
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</li></ul>
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</div>
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</div>
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<div>
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<div class="familylinks">
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<div class="parentlink"><strong>Parent topic:</strong> <a href="dcs-pd-200312001.html">DCS Instance Types</a></div>
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</div>
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</div>
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