5 Things I Learned While Modeling Data in MongoDB
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The document outlines key learnings from modeling data in MongoDB, emphasizing the importance of data organization and handling API data. It discusses strategies like grouping related data together and the potential challenges of data duplication. The content also highlights techniques for data cleaning and optimizing data structures for specific use cases.
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5 Things I Learned While Modeling Data in MongoDB
- 1. 5 Things I Learned While Modeling Data in MongoDB @Lauren_Schaefer | Staff Developer Advocate | MongoDB
- 4. Agenda ● App Demo ● Terms ● Data Model ● 5 Things I Learned
- 5. Agenda ● App Demo ● Terms ● Data Model ● 5 Things I Learned
- 6. 😡
- 8. YouTube API
- 10. 🤩
- 11. 💻
- 13. YouTube API
- 14. YouTube API
- 15. YouTube API
- 17. Agenda ● App Demo ● Terms ● Data Model ● 5 Things I Learned
- 18. Document { first_name: "Lauren", last_name: "Schaefer", tik_tok: "Lauren_Schaefer" } @Lauren_Schaefer
- 19. Collection { first_name: "Lauren", last_name: "Schaefer", tik_tok: "Lauren_Schaefer" } { first_name: "Lauren", last_name: "Schaefer", tik_tok: "Lauren_Schaefer" } { first_name: "Lauren", last_name: "Schaefer", tik_tok: "Lauren_Schaefer" } Users @Lauren_Schaefer
- 21. Agenda ● App Demo ● Terms ● Data Model ● 5 Things I Learned
- 22. The Data Model ● youtube_videos collection @Lauren_Schaefer
- 23. The Data Model ● youtube_videos collection @Lauren_Schaefer
- 24. The Data Model ● youtube_videos collection @Lauren_Schaefer
- 25. The Data Model ● youtube_videos collection @Lauren_Schaefer YouTube API
- 26. The Data Model ● youtube_videos collection @Lauren_Schaefer YouTube API
- 27. The Data Model ● youtube_videos collection @Lauren_Schaefer YouTube API
- 28. { "_id":"8CZs-0it9r4", "kind": "youtube#playlistItem", "isDA": true, ... "snippet": { "publishedAt": 2020-09-30T15:05:30.000+00:00, "channelId": "UCK_m2976Yvbx-TyDLw7n1WA", "title": "Schema Design Anti-Patterns - Part 1", "description": "When modeling your data in MongoDB...", "thumbnails": { ... }, ... } } youtube_videos @Lauren_Schaefer
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- 31. { "_id":"8CZs-0it9r4", "kind": "youtube#playlistItem", "isDA": true, ... "snippet": { "publishedAt": 2020-09-30T15:05:30.000+00:00, "channelId": "UCK_m2976Yvbx-TyDLw7n1WA", "title": "Schema Design Anti-Patterns - Part 1", "description": "When modeling your data in MongoDB...", "thumbnails": { ... }, ... } } youtube_videos @Lauren_Schaefer
- 32. { "_id":"8CZs-0it9r4", "kind": "youtube#playlistItem", "isDA": true, ... "snippet": { "publishedAt": 2020-09-30T15:05:30.000+00:00, "channelId": "UCK_m2976Yvbx-TyDLw7n1WA", "title": "Schema Design Anti-Patterns - Part 1", "description": "When modeling your data in MongoDB...", "thumbnails": { ... }, ... } } youtube_videos @Lauren_Schaefer
- 33. { "_id":"8CZs-0it9r4", "kind": "youtube#playlistItem", "isDA": true, ... "snippet": { "publishedAt": 2020-09-30T15:05:30.000+00:00, "channelId": "UCK_m2976Yvbx-TyDLw7n1WA", "title": "Schema Design Anti-Patterns - Part 1", "description": "When modeling your data in MongoDB...", "thumbnails": { ... }, ... } } youtube_videos @Lauren_Schaefer
- 34. { "_id":"8CZs-0it9r4", "kind": "youtube#playlistItem", "isDA": true, ... "snippet": { "publishedAt": 2020-09-30T15:05:30.000+00:00, "channelId": "UCK_m2976Yvbx-TyDLw7n1WA", "title": "Schema Design Anti-Patterns - Part 1", "description": "When modeling your data in MongoDB...", "thumbnails": { ... }, ... } } youtube_videos @Lauren_Schaefer
- 35. { "_id":"8CZs-0it9r4", "kind": "youtube#playlistItem", "isDA": true, ... "snippet": { "publishedAt": 2020-09-30T15:05:30.000+00:00, "channelId": "UCK_m2976Yvbx-TyDLw7n1WA", "title": "Schema Design Anti-Patterns - Part 1", "description": "When modeling your data in MongoDB...", "thumbnails": { ... }, ... } } youtube_videos @Lauren_Schaefer
- 36. { "_id":"8CZs-0it9r4", "kind": "youtube#playlistItem", "isDA": true, ... "snippet": { "publishedAt": 2020-09-30T15:05:30.000+00:00, "channelId": "UCK_m2976Yvbx-TyDLw7n1WA", "title": "Schema Design Anti-Patterns - Part 1", "description": "When modeling your data in MongoDB...", "thumbnails": { ... }, ... } } youtube_videos @Lauren_Schaefer
- 37. { "_id":"8CZs-0it9r4", "kind": "youtube#playlistItem", "isDA": true, ... "snippet": { "publishedAt": 2020-09-30T15:05:30.000+00:00, "channelId": "UCK_m2976Yvbx-TyDLw7n1WA", "title": "Schema Design Anti-Patterns - Part 1", "description": "When modeling your data in MongoDB...", "thumbnails": { ... }, ... } } youtube_videos @Lauren_Schaefer
- 38. The Data Model ● youtube_videos collection ● youtube_stats collection @Lauren_Schaefer
- 39. The Data Model ● youtube_videos collection ● youtube_stats collection @Lauren_Schaefer
- 40. The Data Model ● youtube_videos collection ● youtube_stats collection @Lauren_Schaefer
- 41. The Data Model ● youtube_videos collection ● youtube_stats collection @Lauren_Schaefer
- 42. The Data Model ● youtube_videos collection ● youtube_stats collection @Lauren_Schaefer
- 43. The Data Model ● youtube_videos collection ● youtube_stats collection @Lauren_Schaefer YouTube API
- 44. The Data Model ● youtube_videos collection ● youtube_stats collection @Lauren_Schaefer YouTube API
- 45. The Data Model ● youtube_videos collection ● youtube_stats collection @Lauren_Schaefer YouTube API
- 46. { "_id": "8CZs-0it9r4_2020_12", "month": 12, "year": 2020, "videoId": "8CZs-0it9r4", "stats": [ { "date": 2020-12-01T00:00:00.000+00:00, "views": 21, "likes": 1 ... }, { "date": 2020-12-02T00:00:00.000+00:00, "views": 29, "likes": 1 ... }, ... ] } youtube_stats @Lauren_Schaefer
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- 48. { "_id": "8CZs-0it9r4_2020_12", "month": 12, "year": 2020, "videoId": "8CZs-0it9r4", "stats": [ { "date": 2020-12-01T00:00:00.000+00:00, "views": 21, "likes": 1 ... }, { "date": 2020-12-02T00:00:00.000+00:00, "views": 29, "likes": 1 ... }, ... ] } youtube_stats @Lauren_Schaefer
- 49. { "_id": "8CZs-0it9r4_2020_12", "month": 12, "year": 2020, "videoId": "8CZs-0it9r4", "stats": [ { "date": 2020-12-01T00:00:00.000+00:00, "views": 21, "likes": 1 ... }, { "date": 2020-12-02T00:00:00.000+00:00, "views": 29, "likes": 1 ... }, ... ] } youtube_stats @Lauren_Schaefer
- 50. { "_id": "8CZs-0it9r4_2020_12", "month": 12, "year": 2020, "videoId": "8CZs-0it9r4", "stats": [ { "date": 2020-12-01T00:00:00.000+00:00, "views": 21, "likes": 1 ... }, { "date": 2020-12-02T00:00:00.000+00:00, "views": 29, "likes": 1 ... }, ... ] } youtube_stats @Lauren_Schaefer
- 51. { "_id": "8CZs-0it9r4_2020_12", "month": 12, "year": 2020, "videoId": "8CZs-0it9r4", "stats": [ { "date": 2020-12-01T00:00:00.000+00:00, "views": 21, "likes": 1 ... }, { "date": 2020-12-02T00:00:00.000+00:00, "views": 29, "likes": 1 ... }, ... ] } youtube_stats @Lauren_Schaefer
- 52. { "_id": "8CZs-0it9r4_2020_12", "month": 12, "year": 2020, "videoId": "8CZs-0it9r4", "stats": [ { "date": 2020-12-01T00:00:00.000+00:00, "views": 21, "likes": 1 ... }, { "date": 2020-12-02T00:00:00.000+00:00, "views": 29, "likes": 1 ... }, ... ] } youtube_stats @Lauren_Schaefer
- 53. { "_id": "8CZs-0it9r4_2020_12", "month": 12, "year": 2020, "videoId": "8CZs-0it9r4", "stats": [ { "date": 2020-12-01T00:00:00.000+00:00, "views": 21, "likes": 1 ... }, { "date": 2020-12-02T00:00:00.000+00:00, "views": 29, "likes": 1 ... }, ... ] } youtube_stats @Lauren_Schaefer
- 54. @Lauren_Schaefer
- 55. @Lauren_Schaefer
- 56. Agenda ● App Demo ● Terms ● Data Model ● 5 Things I Learned
- 57. Duplicating data is scary—even for those of us who have been coaching others to do so @Lauren_Schaefer
- 58. Data that is accessed together should be stored together @Lauren_Schaefer
- 59. Two API Calls ● List of videos ● Video stats @Lauren_Schaefer
- 64. Extended Reference Pattern { "_id":"8CZs-0it9r4", "isDA": true, ... "snippet": { "title": "Schema Design Anti-Patterns - Part 1", "description": "When modeling your data in MongoDB...", "thumbnails": { ... }, ... } } youtube_videos youtube_stats { "_id": "8CZs-0it9r4_2020_12", "month": 12, "year": 2020, "videoId": "8CZs-0it9r4", "title": "Schema Design Anti-Patterns - Part 1", "stats": [ { "date": 2020-12-01, "views": 21, "likes": 1 ... }, ... ] }
- 65. Duplicating data is not as scary when... ● You are confident which data needs to be duplicated ● You use Atlas triggers, change streams, or transactions to make sure the data remains consistent @Lauren_Schaefer
- 66. Cleaning data you receive from APIs will make working with the data easier @Lauren_Schaefer
- 69. { "_id":"8CZs-0it9r4", "kind": "youtube#playlistItem", "isDA": true, ... "snippet": { "publishedAt": "2020-09-30T15:05:30Z", "channelId": "UCK_m2976Yvbx-TyDLw7n1WA", "title": "Schema Design Anti-Patterns - Part 1", "description": "When modeling your data in MongoDB...", "thumbnails": { ... }, ... } } youtube_videos @Lauren_Schaefer
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- 71. @Lauren_Schaefer
- 72. video.snippet.publishedAt = new Date(video.snippet.publishedAt); get_all_youtube_videos @Lauren_Schaefer
- 73. If you're pulling data from an API... ● Consider remodeling or reformatting the data before storing it @Lauren_Schaefer
- 74. Optimizing for your use case is really hard when you don't fully know what your use case will be @Lauren_Schaefer
- 77. @Lauren_Schaefer
- 78. Data that is accessed together should be stored together @Lauren_Schaefer
- 79. Data that is accessed together should be stored together @Lauren_Schaefer
- 80. @Lauren_Schaefer
- 81. { "_id": "8CZs-0it9r4_2020_12", "month": 12, "year": 2020, "videoId": "8CZs-0it9r4", "fiscal_year_quarter": "FY21Q4", "stats": [ { "date": 2020-12-01T00:00:00.000+00:00, "views": 21, "likes": 1 ... }, { "date": 2020-12-02T00:00:00.000+00:00, "views": 29, "likes": 1 ... }, ... ] } youtube_stats @Lauren_Schaefer
- 82. When modeling data in MongoDB... ● Model for your use case ● Remodel easily due to MongoDB's flexible schema @Lauren_Schaefer
- 83. There is no "right way" to model your data @Lauren_Schaefer
- 87. 💪
- 88. 🤔
- 89. 🆗
- 90. When modeling data in MongoDB... ● Don't let the flexibility freak you out ● Use schema validation @Lauren_Schaefer
- 91. Determine how much you want to tweak your data model based on the ease of working with the data and your performance requirements @Lauren_Schaefer
- 92. There is no "right way" to model your data @Lauren_Schaefer
- 93. When is your data model good enough? @Lauren_Schaefer
- 94. When is your data model good enough? ❏ Is the ease of working with the data good enough? @Lauren_Schaefer
- 95. When is your data model good enough? ✓ Is the ease of working with the data good enough? @Lauren_Schaefer
- 96. When is your data model good enough? ✓ Is the ease of working with the data good enough? ❏ Is the app's performance good enough? @Lauren_Schaefer
- 97. When is your data model good enough? ✓ Is the ease of working with the data good enough? ✓ Is the app's performance good enough? @Lauren_Schaefer
- 98. @Lauren_Schaefer
- 99. @Lauren_Schaefer
- 100. Duplicating data is scary—even for those of us who have been coaching others to do so @Lauren_Schaefer
- 101. Cleaning data you receive from APIs will make working with the data easier @Lauren_Schaefer
- 102. Optimizing for your use case is really hard when you don't fully know what your use case will be @Lauren_Schaefer
- 103. There is no "right way" to model your data @Lauren_Schaefer
- 104. Determine how much you want to tweak your data model based on the ease of working with the data and your performance requirements @Lauren_Schaefer
- 105. @Lauren_Schaefer
- 106. Data Modeling Resources Free MongoDB University Course: M320: Data Modeling Article Series: MongoDB Schema Design Patterns YouTube Video Series: MongoDB Schema Design Anti-Patterns Article Series: MongoDB Schema Design Anti-Patterns Got a Question? MongoDB Community @Lauren_Schaefer
- 107. Remember 💡 Every use case is different, so every data model will be different. Focus on how your app will use the data. @Lauren_Schaefer
- 108. Remember 💡 Every use case is different, so every data model will be different. Focus on how your app will use the data. Let's connect on social linktr.ee/lauren_schaefer @Lauren_Schaefer