thoughtworks_Neo4j：绘制ThoughtWorks技术雷达图

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为了获得圣诞节假期的乐趣&＃xff0c;我认为在ThoughtWorks Technology Radar上创建不同点的图形以及建议随时间的变化是很酷的。

我编写了一个脚本来提取每个blip&＃xff08;例如.NET Core &＃xff09;以及在每个雷达中出现的建议。我最终得到了一个CSV文件 &＃xff1a;

|----------------------------------------------&＃43;----------&＃43;-------------|
| technology | date | suggestion |
|----------------------------------------------&＃43;----------&＃43;-------------|
| AppHarbor | Mar 2012 | Trial |
| Accumulate-only data | Nov 2015 | Assess |
| Accumulate-only data | May 2015 | Assess |
| Accumulate-only data | Jan 2015 | Assess |
| Buying solutions you can only afford one of | Mar 2012 | Hold |
|----------------------------------------------&＃43;----------&＃43;-------------|

然后&＃xff0c;我编写了Cypher脚本来创建以下图形模型&＃xff1a;

WITH ["Hold", "Assess", "Trial", "Adopt"] AS positions
UNWIND RANGE (0, size(positions) - 2) AS index
WITH positions[index] AS pos1, positions[index &＃43; 1] AS pos2
MERGE (position1:Position {value: pos1})
MERGE (position2:Position {value: pos2})
MERGE (position1)-[:NEXT]->(position2);load csv with headers from "file:///blips.csv" AS row
MATCH (position:Position {value: row.suggestion })
MERGE (tech:Technology {name: row.technology })
MERGE (date:Date {value: row.date})
MERGE (recommendation:Recommendation {id: tech.name &＃43; "_" &＃43; date.value &＃43; "_" &＃43; position.value})
MERGE (recommendation)-[:ON_DATE]->(date)
MERGE (recommendation)-[:POSITION]->(position)
MERGE (recommendation)-[:TECHNOLOGY]->(tech);match (date:Date)
SET date.timestamp &＃61; apoc.date.parse(date.value, "ms", "MMM yyyy");MATCH (date:Date)
WITH date
ORDER BY date.timestamp
WITH COLLECT(date) AS dates
UNWIND range(0, size(dates)-2) AS index
WITH dates[index] as month1, dates[index&＃43;1] AS month2
MERGE (month1)-[:NEXT]->(month2);MATCH (tech)<-[:TECHNOLOGY]-(reco:Recommendation)-[:ON_DATE]->(date)
WITH tech, reco, date
ORDER BY tech.name, date.timestamp
WITH tech, COLLECT(reco) AS recos
UNWIND range(0, size(recos)-2) AS index
WITH recos[index] AS reco1, recos[index&＃43;1] AS reco2
MERGE (reco1)-[:NEXT]->(reco2);

请注意&＃xff0c;我安装了APOC过程库&＃xff0c;以便可以使用apoc.date.parse函数将日期的字符串表示形式转换为时间戳。 blips.csv文件需要进入Neo4j的导入目录。

现在&＃xff0c;我们正在阅读以编写一些查询。

对于特定技术&＃xff0c;技术雷达有4个职位&＃xff1a;保留&＃xff0c;评估&＃xff0c;试用和采用&＃xff1a;

• 保留&＃xff1a;谨慎处理
• 评估&＃xff1a;值得探索&＃xff0c;目的是了解它将如何影响您的企业。
• 试用&＃xff1a;值得追求。 了解如何建立此功能非常重要。 企业应该在可以处理风险的项目上尝试使用该技术。
• 采用&＃xff1a;我们强烈认为行业应采用这些项目。 我们在项目中适当时使用它们。

我很好奇是否曾经有过一种技术&＃xff0c;其建议最初是“保留”&＃xff0c;后来又变成了“评估”。 我写了以下查询来找出&＃xff1a;

MATCH (pos1:Position {value:"Hold"})<-[:POSITION]-(reco)-[:TECHNOLOGY]->(tech),(pos2:Position {value:"Assess"})<-[:POSITION]-(otherReco)-[:TECHNOLOGY]->(tech),(reco)-[:ON_DATE]->(recoDate),(otherReco)-[:ON_DATE]->(otherRecoDate)
WHERE (reco)-[:NEXT]->(otherReco)
RETURN tech.name AS technology, otherRecoDate.value AS dateOfChange;╒════════════╤══════════════╕
│"technology"│"dateOfChange"│
╞════════════╪══════════════╡
│"Azure" │"Aug 2010" │
└────────────┴──────────────┘

只有天蓝色 &＃xff01; 该页面没有任何有关2010年4月最初的“保留”建议的解释&＃xff0c;该建议大概是在“云”成为主流之前。 那反过来呢&＃xff1f; 是否有最初建议“评估”但后来建议“保留”的技术&＃xff1f;

MATCH (pos1:Position {value:"Assess"})<-[:POSITION]-(reco)-[:TECHNOLOGY]->(tech),(pos2:Position {value:"Hold"})<-[:POSITION]-(otherReco)-[:TECHNOLOGY]->(tech),(reco)-[:ON_DATE]->(recoDate),(otherReco)-[:ON_DATE]->(otherRecoDate)
WHERE (reco)-[:NEXT]->(otherReco)
RETURN tech.name AS technology, otherRecoDate.value AS dateOfChange;╒═══════════════════════════════════╤══════════════╕
│"technology" │"dateOfChange"│
╞═══════════════════════════════════╪══════════════╡
│"RIA" │"Apr 2010" │
├───────────────────────────────────┼──────────────┤
│"Backbone.js" │"Oct 2012" │
├───────────────────────────────────┼──────────────┤
│"Pace-layered Application Strategy"│"Nov 2015" │
├───────────────────────────────────┼──────────────┤
│"SPDY" │"May 2015" │
├───────────────────────────────────┼──────────────┤
│"AngularJS" │"Nov 2016" │
└───────────────────────────────────┴──────────────┘

其中有一些是Javascript库/框架&＃xff0c;因此现在建议使用React代替。 让我们检查&＃xff1a;

MATCH (t:Technology)<-[:TECHNOLOGY]-(reco)-[:ON_DATE]->(date), (reco)-[:POSITION]->(pos)
WHERE t.name contains "React.js"
RETURN pos.value, date.value
ORDER BY date.timestamp╒═══════════╤════════════╕
│"pos.value"│"date.value"│
╞═══════════╪════════════╡
│"Assess" │"Jan 2015" │
├───────────┼────────────┤
│"Trial" │"May 2015" │
├───────────┼────────────┤
│"Trial" │"Nov 2015" │
├───────────┼────────────┤
│"Adopt" │"Apr 2016" │
├───────────┼────────────┤
│"Adopt" │"Nov 2016" │
└───────────┴────────────┘

灰烬也很受欢迎&＃xff1a;

MATCH (t:Technology)<-[:TECHNOLOGY]-(reco)-[:ON_DATE]->(date), (reco)-[:POSITION]->(pos)
WHERE t.name contains "Ember"
RETURN pos.value, date.value
ORDER BY date.timestamp╒═══════════╤════════════╕
│"pos.value"│"date.value"│
╞═══════════╪════════════╡
│"Assess" │"May 2015" │
├───────────┼────────────┤
│"Assess" │"Nov 2015" │
├───────────┼────────────┤
│"Trial" │"Apr 2016" │
├───────────┼────────────┤
│"Adopt" │"Nov 2016" │
└───────────┴────────────┘

让我们进行不同的切线研究&＃xff0c;看看最近的雷达中引入了多少种技术&＃xff1f;

MATCH (date:Date {value: "Nov 2016"})<-[:ON_DATE]-(reco)
WHERE NOT (reco)<-[:NEXT]-()
RETURN COUNT(*) ╒══════════╕
│"COUNT(*)"│
╞══════════╡
│"45" │
└──────────┘

哇&＃xff0c;有45件事&＃xff01; 它们如何分散在不同的职位上&＃xff1f;

MATCH (date:Date {value: "Nov 2016"})<-[:ON_DATE]-(reco)-[:TECHNOLOGY]->(tech), (reco)-[:POSITION]->(position)
WHERE NOT (reco)<-[:NEXT]-()
WITH position, COUNT(*) AS count, COLLECT(tech.name) AS technologies
ORDER BY LENGTH((position)-[:NEXT*]->()) DESC
RETURN position.value, count, technologies╒════════════════╤═══════╤══════════════════════════════════════════════╕
│"position.value"│"count"│"technologies" │
╞════════════════╪═══════╪══════════════════════════════════════════════╡
│"Hold" │"1" │["Anemic REST"] │
├────────────────┼───────┼──────────────────────────────────────────────┤
│"Assess" │"28" │["Nuance Mix","Micro frontends","Three.js","Sc│
│ │ │ikit-learn","WebRTC","ReSwift","Vue.js","Elect│
│ │ │ron","Container security scanning","wit.ai","D│
│ │ │ifferential privacy","Rapidoid","OpenVR","AWS │
│ │ │Application Load Balancer","Tarantool","IndiaS│
│ │ │tack","Ethereum","axios","Bottled Water","Cass│
│ │ │andra carefully","ECMAScript 2017","FBSnapshot│
│ │ │Testcase","Client-directed query","JuMP","Cloj│
│ │ │ure.spec","HoloLens","Android-x86","Physical W│
│ │ │eb"] │
├────────────────┼───────┼──────────────────────────────────────────────┤
│"Trial" │"13" │["tmate","Lightweight Architecture Decision Re│
│ │ │cords","APIs as a product","JSONassert","Unity│
│ │ │ beyond gaming","Galen","Enzyme","Quick and Ni│
│ │ │mble","Talisman","fastlane","Auth0","Pa11y","P│
│ │ │hoenix"] │
├────────────────┼───────┼──────────────────────────────────────────────┤
│"Adopt" │"3" │["Grafana","Babel","Pipelines as code"] │
└────────────────┴───────┴──────────────────────────────────────────────┘

假期中有很多新事物可供探索&＃xff01; 如果您想使用它们&＃xff0c;则本文中使用的CSV文件&＃xff0c;导入脚本和查询都可以在github上找到 。

翻译自: https://www.javacodegeeks.com/2016/12/neo4j-graphing-thoughtworks-technology-radar.html

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