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Reorder sidebar (#1787)
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* Move sources and destinations to the top level
* Update the css
* Update sidebars.js
* Adjust icons

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Co-authored-by: Violetta Mishechkina <[email protected]>
Co-authored-by: akelad <[email protected]>
Co-authored-by: Anton Burnashev <[email protected]>
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4 people authored Sep 14, 2024
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4 changes: 2 additions & 2 deletions docs/website/docs/reference/performance.md
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---
title: Performance
title: Optimizing dlt
description: Scale-up, parallelize and finetune dlt pipelines
keywords: [scaling, parallelism, finetuning]
---

# Performance
# Optimizing dlt

## Yield pages instead of rows

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5 changes: 2 additions & 3 deletions docs/website/docs/tutorial/load-data-from-an-api.md
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Expand Up @@ -574,9 +574,8 @@ Interested in learning more? Here are some suggestions:
- [Run in production: inspecting, tracing, retry policies and cleaning up](../running-in-production/running).
- [Run resources in parallel, optimize buffers and local storage](../reference/performance.md)
- [Use REST API client helpers](../general-usage/http/rest-client.md) to simplify working with REST APIs.
3. Check out our [how-to guides](../walkthroughs) to get answers to some common questions.
4. Explore [destinations](../dlt-ecosystem/destinations/) and [sources](../dlt-ecosystem/verified-sources/) provided by us and community.
5. Explore the [Examples](../examples) section to see how dlt can be used in real-world scenarios
3. Explore [destinations](../dlt-ecosystem/destinations/) and [sources](../dlt-ecosystem/verified-sources/) provided by us and community.
4. Explore the [Examples](../examples) section to see how dlt can be used in real-world scenarios



4 changes: 2 additions & 2 deletions docs/website/docs/walkthroughs/share-a-dataset.md
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---
title: 'Share a dataset: DuckDB -> BigQuery'
title: 'Moving from local to production'
description: Share a local dataset by moving it to BigQuery
keywords: [how to, share a dataset]
---

# Share a dataset: DuckDB -> BigQuery
# Moving from local to production

In previous how-to guides you used the local stack to create and run your pipeline. This saved you
the headache of setting up cloud account, credentials and often also money. Our choice for local
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