From 000a9418338982c08a2e5e4e3908e717f7677c57 Mon Sep 17 00:00:00 2001 From: Zheng-Xian Li Date: Fri, 26 May 2023 00:15:31 +0800 Subject: [PATCH 1/3] [BALANCER] `BackboneImbalanceScenario` Experiment --- docs/balancer/experiment_3.md | 266 +++++++++++++++++++++ docs/balancer/resources/experiment_3_1.png | Bin 0 -> 181789 bytes docs/balancer/resources/experiment_3_2.png | Bin 0 -> 151227 bytes docs/balancer/resources/experiment_3_3.png | Bin 0 -> 24501 bytes docs/balancer/resources/experiment_3_4.png | Bin 0 -> 24040 bytes docs/balancer/resources/experiment_3_5.png | Bin 0 -> 98229 bytes docs/balancer/resources/experiment_3_6.png | Bin 0 -> 199004 bytes docs/balancer/resources/experiment_3_7.png | Bin 0 -> 165452 bytes docs/balancer/resources/experiment_3_8.png | Bin 0 -> 143753 bytes 9 files changed, 266 insertions(+) create mode 100644 docs/balancer/experiment_3.md create mode 100644 docs/balancer/resources/experiment_3_1.png create mode 100644 docs/balancer/resources/experiment_3_2.png create mode 100644 docs/balancer/resources/experiment_3_3.png create mode 100644 docs/balancer/resources/experiment_3_4.png create mode 100644 docs/balancer/resources/experiment_3_5.png create mode 100644 docs/balancer/resources/experiment_3_6.png create mode 100644 docs/balancer/resources/experiment_3_7.png create mode 100644 docs/balancer/resources/experiment_3_8.png diff --git a/docs/balancer/experiment_3.md b/docs/balancer/experiment_3.md new file mode 100644 index 0000000000..db25418b41 --- /dev/null +++ b/docs/balancer/experiment_3.md @@ -0,0 +1,266 @@ +# Astraea Balancer 測試 (Data Skew 情境) #3 + +這個實驗是基於 [Backbone Imbalance Scenario](https://github.com/skiptests/astraea/issues/1424) 叢集情境測試, +這個情境模擬叢集中存在一個非常高流量的骨幹 ,且該 Topic 有特定的 Record Key 有較高的出現頻率 +(基於 Zipfian Distribution),這導致該 Topic 的 Partition 之間存在負載不均的現象。 + +這個實驗中我們實驗了 Astraea Balancer 對該叢集做負載平衡,得到了以下的結果。 + +* 節點讀取效能平衡程度改善 78 % +* 節點寫入效能平衡程度改善 97.6 % +* 每個節點負責的 Partition 數量介於平均量 ± 30% + +## 叢集硬體環境 + +這次實驗中總共涉及 15 台設備 + +* 7 台 Kafka Broker 節點, 其中 1 台擔任 Controller。 +* 7 台 Kafka Producer/Consumer 節點 +* 1 台普通的電腦,執行 Astraea Balancer + +下圖為網路示意圖: + +``` + [500 Mbits Router] + ┌──────────────────┐ + [10 Gbits Switch] │ │ + ┌─────┬─────┬─────┬─────┬─────┬─────┬─────┬─────┬─────┬─────┬─────┬──┴──┬─────┐ │ + B1 B2 B3 B4 B5 B6 Ctl P1 C1 PC2 PC3 PC4 PC5 PC6 Balancer +``` + +每個機器負責執行的軟體: + +* B1: Kafka Broker, Node Exporter +* B2: Kafka Broker, Node Exporter +* B3: Kafka Broker, Node Exporter +* B4: Kafka Broker, Node Exporter +* B5: Kafka Broker, Node Exporter +* B6: Kafka Broker, Node Exporter +* Ctl: Kafka KRaft Controller, Prometheus, Node Exporter +* P1: Performance Tool(Producer, Skew Data Source), Node Exporter +* C1: Performance Tool(Consumer, Skew Data Source), Node Exporter +* PC2: Performance Tool(Producer & Consumer), Node Exporter +* PC3: Performance Tool(Producer & Consumer), Node Exporter +* PC4: Performance Tool(Producer & Consumer), Node Exporter +* PC5: Performance Tool(Producer & Consumer), Node Exporter +* PC6: Performance Tool(Producer & Consumer), Node Exporter +* Balancer: 執行 Astraea Balancer 的機器 + +下表為 B1, B2, B3, B4, B5, B6 的硬體規格: + +| 硬體項目 | 型號 | +|------|--------------------------------------------------------------------------| +| CPU | Intel i9-12900K CPU 3.2G(5.2G)/30M/UHD770/125W | +| 主機板 | 華碩 ROG STRIX Z690-G GAMING WIFI(M-ATX/1H1P/Intel 2.5G+Wi-Fi 6E)14+1相數位供電 | +| 記憶體 | 美光Micron Crucial 32GB DDR5 4800 | +| 硬碟*3 | 威剛XPG SX8200Pro 1TB/M.2 2280/讀:3500M/寫:3000M/TLC/SMI控 | +| 網路卡 | XG-C100C [10Gigabit埠] RJ45單埠高速網路卡/PCIe介面 | + +下表為 Ctl(Kafka KRaft Controller) 的硬體規格: + +| 硬體項目 | 型號 | +|-------|-------------------------------------------------------| +| CPU | Intel i7-11700K [8核/16緒] 3.6GHz(5.0G)/16M/UHD750/125W | +| 主機板 | 技嘉Z590M GAMING X(M-ATX/1H1P/Realtek 2.5G)12+1相數位供電 | +| 記憶體 | 金士頓 32G(16G2)D4-3200(KF432C16BB1K2/32)(10248) | +| 硬碟*2 | ADATA 威剛 XPG SX8200Pro 1 TB M.2 2280 PCIe SSD * 2 | +| 散熱器 | 快睿H7 散熱器/蜂巢式鰭片/6mm導管*3/高14.5cm/TDP:140W | +| 電源供應器 | Antec NE550G(550W) 金牌/半模/全日系/LLC+DC-DC | +| 網卡 | XG-C100C [10Gigabit埠] RJ45單埠高速網路卡/PCIe介面 | + +下表為 P1, C1, PC2, PC3, PC4, PC5, PC6 的硬體規格: + +| 硬體項目 | 型號 | +|-------|---------------------------------------------------| +| CPU | Intel Core i7-13700K Processor | +| 主機板 | 華碩 PRIME Z790-P WIFI-CSM | +| 記憶體 | 海盜船 Corsair 統治者 DDR5-5600 16GB * 2 | +| 硬碟*2 | ADATA 威剛 XPG SX8200Pro 1 TB M.2 2280 PCIe SSD * 2 | +| 散熱器 | Cooler Master MasterLiquid ML240L V2 ARGB | +| 電源供應器 | Cooler Master New GX 金牌 850W | +| 網卡 | XG-C100C [10Gigabit埠] RJ45單埠高速網路卡/PCIe介面 | + +下表為執行 Balancer 的設備之硬體規格: + +| 硬體項目 | 型號 | +|------|------------------------------------------------------| +| CPU | 11th Gen Intel(R) Core(TM) i7-11700K @ 3.60GHz | +| 記憶體 | KLEVV DIMM DDR4 Synchronous 2667 MHz (0.4 ns) 16GB*2 | +| 主機板 | MAG B560 TOMAHAWK WIFI (MS-7D15) | + +## 叢集軟體環境 + +* Apache Kafka version 3.4.0, 各個節點包含 3 個 log dir,每個有 844GB 空間的 SSD +* Astraea Balancer (revision ced840f9ded6e4167ccbbc86a20f79f7ec6be0c0) + +### 建立 Kafka 叢集 + +請依照上述的環境建立叢集,您可以使用專案內的 +[./docker/start_broker.sh](https://github.com/skiptests/astraea/blob/ced840f9ded6e4167ccbbc86a20f79f7ec6be0c0/docker/start_broker.sh) 和 +[./docker/start_controller.sh](https://github.com/skiptests/astraea/blob/ced840f9ded6e4167ccbbc86a20f79f7ec6be0c0/docker/start_controller.sh) 來建立叢集。 + +## 效能資料攝取 + +整個實驗的效能指標數據源自每個 Kafka Broker 的 JMX 資訊,這些資訊透過 jmx_exporter 輸出成 Prometheus 能夠接受的格式, +接著以 Grafana 繪圖觀察。實驗過程中我們也有關心實際硬體資源的使用情況,這部分我們透過在每個硬體設備啟動的 node exporter 和 Prometheus, +進行底層硬體效能資料的攝取。 + +您可以使用專案內的 +[./docker/start_node_exporter.sh](https://github.com/skiptests/astraea/blob/ced840f9ded6e4167ccbbc86a20f79f7ec6be0c0/docker/start_node_exporter.sh), +[./docker/start_prometheus.sh](https://github.com/skiptests/astraea/blob/ced840f9ded6e4167ccbbc86a20f79f7ec6be0c0/docker/start_prometheus.sh) 和 +[./docker/start_grafana.sh](https://github.com/skiptests/astraea/blob/ced840f9ded6e4167ccbbc86a20f79f7ec6be0c0/docker/start_grafana.sh) 來建構監控環境。 + +## 建立情境 + +參考 https://github.com/skiptests/astraea/issues/1424 敘述的情境,建立對應的實驗環境 + +## 執行實驗 + +首先取得 Astraea Project + +```script +git clone https://github.com/skiptests/astraea.git +cd astraea +git checkout ced840f9ded6e4167ccbbc86a20f79f7ec6be0c0 +``` + +接著執行 Astraea Web Service,Astraea Web Service 提供一系列的功能,能幫助我們對 Kafka 進行管理和操作。 + +執行 `./gradlew run --args="web --bootstrap.servers "` 來使用 web service,其中 `` 是 +Kafka 對外服務的網路位置。 + +宣告要使用的 Sensor + +```shell +curl -X POST --location "http://localhost:8001/sensors" \ + -H "Content-Type: application/json" \ + -d '{ + ' "costs": [ + "org.astraea.common.cost.NetworkIngressCost", + "org.astraea.common.cost.NetworkEgressCost" + ] + }' +``` + +對 Astraea Balancer 發送 `POST /balancer` HTTP Request, 請 Balancer 計算負載平衡計劃。 + +```shell +curl -X POST --location "http://localhost:8001/balancer" \ + -H "Content-Type: application/json" \ + -d '{ + "timeout": "120s", + "balancer": "org.astraea.common.balancer.algorithms.GreedyBalancer", + "balancerConfig": { + "shuffle.tweaker.min.step": 1, + "shuffle.tweaker.max.step": 5 + }, + "clusterCosts": [ + { "cost": "org.astraea.common.cost.NetworkIngressCost", "weight": 1 }, + { "cost": "org.astraea.common.cost.NetworkEgressCost", "weight": 1 } + ] + }' +``` + +執行完成後後會在 terminal 上印出負載平衡計劃的編號: + +```shell +# Something like this: {"id":"9b25bf14-a885-4c5b-97bf-59ff025b61d2"} +{"id":"Your-Balance-Plan-Id"} +``` + +之後可以透過 `GET /balancer/Your-Balance-Plan-Id` 來查詢關於這個計劃的狀態,比如這個計劃是否生成完成,或是已經排程執行。 + +```shell +curl -X GET http://localhost:8001/balancer/46ecf6e7-aa28-4f72-b1b6-a788056c122a + +# { +# "id": "46ecf6e7-aa28-4f72-b1b6-a788056c122a", // 計劃的編號 +# // 搜尋計劃細節 +# "config": { +# "balancer": "org.astraea.common.balancer.algorithms.GreedyBalancer", +# "function": "WeightCompositeClusterCostFunction[{\"NetworkIngressCost\" weight 1.0}, {\"NetworkEgressCost\" weight 1.0}]", +# "timeout": "120000ms" +# }, +# "phase": "Searched", // 計劃狀態 +# "plan": { ... } // 關於這個計劃的細節,計劃生成後才會有此詳細資訊 +# } +``` + +如果 `GET /balancer/Your-Balance-Plan-Id` 回傳結果中 `phase` 為 `Searched`, 則代表計劃已經完成生成。 + +> 如果計劃生成失敗,可以檢查 `exception` 欄位的訊息,或是查看 Web Service 是否有印出錯誤的資訊,來做進一步的診斷。 + +計劃成功生成後,可以透過 `PUT /balancer` 來執行負載平衡的計劃。 + +這個實驗的情境是執行於叢集的歲修期間,因此這個時候叢集的 Client 會暫時停止運作。 + +等 Client 停止運作後執行下面的 PUT Request 來執行 Balancer 負載優化計劃。 + +```shell +curl -X PUT http://localhost:8001/balancer \ + -H "Content-Type: application/json" \ + -d '{ "id": "Your-Balance-Plan-Id" }' +``` + +過程中可以透過 `GET /balancer/Your-Balance-Plan-Id` 來檢查執行的狀態,當輸出結果中的 `phase` 為 `Executed` 時意味著計劃已經完成執行。 + +> 如果計劃執行失敗,可以檢查 `exception` 欄位的訊息,或是查看 Web Service 是否有印出錯誤的資訊,來做進一步的診斷。 + +> 詳細的 `/balancer` API 文件,可以參考[這裡](https://github.com/skiptests/astraea/blob/ced840f9ded6e4167ccbbc86a20f79f7ec6be0c0/docs/web_server/web_api_balancer_chinese.md) + +## 實驗執行結果 + +### Broker Ingress + +![broker ingress](./resources/experiment_3_1.png) + +| 狀態 | 節點最高吞吐量 | 節點最低吞吐量 | 負載平衡程度 | +|-----|----------|----------|--------| +| 執行前 | 529 MB/s | 333 MB/s | 37.0 % | +| 執行後 | 404 MB/s | 371 MB/s | 8.1 % | + +節點讀取效能平衡程度改善 78 % + +### Broker Egress + +![broker egress](./resources/experiment_3_2.png) + +| 狀態 | 節點最高吞吐量 | 節點最低吞吐量 | 負載不平衡比例 | +|-----|----------|----------|---------| +| 執行前 | 666 MB/s | 468 MB/s | 29.7 % | +| 執行後 | 517 MB/s | 513 MB/s | 0.7 % | + +節點寫入效能平衡程度改善 97.6 % + +### Partition 數量 + +![partition count (before)](./resources/experiment_3_3.png) + +![partition count (after)](./resources/experiment_3_4.png) + +| 狀態 | 節點最高 Partition 數量 | 節點最低 Partition 數量 | 平均值 | 最大差異% | +|-----|-------------------|-------------------|------|--------| +| 執行前 | 1693 | 1649 | 1669 | 1.4% | +| 執行後 | 1832 | 1378 | 1669 | 17.4 % | + +每個節點負責的 Partition 數量介於平均量 ± 30% + +### Ongoing Reassignment + +![ongoing reassignment bandwidth](./resources/experiment_3_5.png) + +總共觸發了一次 Reassignment,執行時間約 5 分 30 秒 + +### Producer/Consumer Client 流量 + +![producer bandwidth](./resources/experiment_3_6.png) +![consumer bandwidth](./resources/experiment_3_7.png) + +整個執行過程沒有額外瓶頸導致的吞吐量下降現象。 + +### 節點的硬碟讀寫吞吐量 + +![broker disk read/write](./resources/experiment_3_8.png) + +可以注意到節點的硬碟,只有在搬移時出現讀取的流量,如果您重現實驗時,在搬移之外的階段就出現讀取的吞吐量, +這意味著目前的實驗環境 Consumer 可能沒辦法跟上消費的進度,此時可能要檢視硬體配置或 Producer/Consumer 參數是否正確。 diff --git a/docs/balancer/resources/experiment_3_1.png b/docs/balancer/resources/experiment_3_1.png new file mode 100644 index 0000000000000000000000000000000000000000..69cd10e6ce391487dc0499938308a957dd39a6d9 GIT binary patch literal 181789 zcmd42by!qw_cn})fPe_nA%lRlw6x05E#2MSF{B6#E!`j;LrBLEBGMg0he&sKy&Jsm z`+45)`_=az-yiQj1ljwVJy)%@uC>l{tw3365p+~SR3s!MbTLuzMAJp-SfxHVDHK2;}0HJ+o z)skR9K?r~NU|EzM{ZS$R$k<#?NKDaDUQshIWt;{P2L(evt9+m!ulmyQ;aHL-f%2f| z_(EUrc@+Nh#E`WU``TIa<(`CtWJo>Rfn%z@3O~aXO^jWNv+igZ(sK{M~}|{ax;GsY+q4lm1wX5tA&BRp~Ye3kq>r`Pr;ugT^5-E{9>J^y5KH+0fYskej>!9LvD>Jv=j 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Date: Fri, 26 May 2023 14:49:35 +0800 Subject: [PATCH 2/3] Revise --- docs/balancer/experiment_3.md | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/docs/balancer/experiment_3.md b/docs/balancer/experiment_3.md index db25418b41..beb1bac8a0 100644 --- a/docs/balancer/experiment_3.md +++ b/docs/balancer/experiment_3.md @@ -6,7 +6,7 @@ 這個實驗中我們實驗了 Astraea Balancer 對該叢集做負載平衡,得到了以下的結果。 -* 節點讀取效能平衡程度改善 78 % +* 節點讀取效能平衡程度改善 78.1 % * 節點寫入效能平衡程度改善 97.6 % * 每個節點負責的 Partition 數量介於平均量 ± 30% @@ -219,7 +219,7 @@ curl -X PUT http://localhost:8001/balancer \ | 執行前 | 529 MB/s | 333 MB/s | 37.0 % | | 執行後 | 404 MB/s | 371 MB/s | 8.1 % | -節點讀取效能平衡程度改善 78 % +節點讀取效能平衡程度改善 78.1 % ### Broker Egress From b7d725541072bee6e3b23c3a653cba6cef7eed03 Mon Sep 17 00:00:00 2001 From: Zheng-Xian Li Date: Sat, 27 May 2023 12:58:01 +0800 Subject: [PATCH 3/3] Revise --- docs/balancer/README.md | 1 + docs/balancer/experiment_3.md | 39 +++++++++++++++++++---------------- 2 files changed, 22 insertions(+), 18 deletions(-) diff --git a/docs/balancer/README.md b/docs/balancer/README.md index ee168bd59b..e488af470a 100644 --- a/docs/balancer/README.md +++ b/docs/balancer/README.md @@ -13,3 +13,4 @@ Astraea Balancer 是一個 Kafka 節點端的負載優化框架,其透過使 * Astraea Balancer 實驗報告 * [實驗報告#1](experiment_1.md) * [實驗報告#2](experiment_2.md) + * [實驗報告#3 (Data Skew 情境)](experiment_3.md) diff --git a/docs/balancer/experiment_3.md b/docs/balancer/experiment_3.md index beb1bac8a0..6c9d066958 100644 --- a/docs/balancer/experiment_3.md +++ b/docs/balancer/experiment_3.md @@ -1,4 +1,4 @@ -# Astraea Balancer 測試 (Data Skew 情境) #3 +# Astraea Balancer 測試 #3 (Data Skew 情境) 這個實驗是基於 [Backbone Imbalance Scenario](https://github.com/skiptests/astraea/issues/1424) 叢集情境測試, 這個情境模擬叢集中存在一個非常高流量的骨幹 ,且該 Topic 有特定的 Record Key 有較高的出現頻率 @@ -25,26 +25,28 @@ ┌──────────────────┐ [10 Gbits Switch] │ │ ┌─────┬─────┬─────┬─────┬─────┬─────┬─────┬─────┬─────┬─────┬─────┬──┴──┬─────┐ │ - B1 B2 B3 B4 B5 B6 Ctl P1 C1 PC2 PC3 PC4 PC5 PC6 Balancer + B1 B2 B3 B4 B5 B6 Ctl Ps Ps Cs PC1 PC2 PC3 PC4 Balancer ``` 每個機器負責執行的軟體: -* B1: Kafka Broker, Node Exporter -* B2: Kafka Broker, Node Exporter -* B3: Kafka Broker, Node Exporter -* B4: Kafka Broker, Node Exporter -* B5: Kafka Broker, Node Exporter -* B6: Kafka Broker, Node Exporter -* Ctl: Kafka KRaft Controller, Prometheus, Node Exporter -* P1: Performance Tool(Producer, Skew Data Source), Node Exporter -* C1: Performance Tool(Consumer, Skew Data Source), Node Exporter -* PC2: Performance Tool(Producer & Consumer), Node Exporter -* PC3: Performance Tool(Producer & Consumer), Node Exporter -* PC4: Performance Tool(Producer & Consumer), Node Exporter -* PC5: Performance Tool(Producer & Consumer), Node Exporter -* PC6: Performance Tool(Producer & Consumer), Node Exporter -* Balancer: 執行 Astraea Balancer 的機器 +| Server | Software | +|----------|--------------------------------------------------------------| +| B1 | Kafka Broker, Node Exporter | +| B2 | Kafka Broker, Node Exporter | +| B3 | Kafka Broker, Node Exporter | +| B4 | Kafka Broker, Node Exporter | +| B5 | Kafka Broker, Node Exporter | +| B6 | Kafka Broker, Node Exporter | +| Ctl | Kafka KRaft Controller, Prometheus, Node Exporter | +| Ps | Performance Tool(Producer1, Skew Data Source), Node Exporter | +| Ps | Performance Tool(Producer2, Skew Data Source), Node Exporter | +| Cs | Performance Tool(Consumer, Skew Data Source), Node Exporter | +| PC1 | Performance Tool(Producer & Consumer), Node Exporter | +| PC2 | Performance Tool(Producer & Consumer), Node Exporter | +| PC3 | Performance Tool(Producer & Consumer), Node Exporter | +| PC4 | Performance Tool(Producer & Consumer), Node Exporter | +| Balancer | 執行 Astraea Balancer 的機器 | 下表為 B1, B2, B3, B4, B5, B6 的硬體規格: @@ -157,7 +159,8 @@ curl -X POST --location "http://localhost:8001/balancer" \ "clusterCosts": [ { "cost": "org.astraea.common.cost.NetworkIngressCost", "weight": 1 }, { "cost": "org.astraea.common.cost.NetworkEgressCost", "weight": 1 } - ] + ], + "moveCosts": [] }' ```

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