chore: remove all refs to azure CDN - #2326
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ranadeepsingh
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## Summary Repair current and versioned R setup guidance so each release installs its six published, version-matched component archives and resolves SynapseML JVM artifacts through Blob Storage. Document the compatibility bypass required by already-published wrappers, correct the Databricks setup and LightGBM example, remove invalid HTML-page Maven repositories from the Docker demo, and add generator/docs regressions. ## Prompting Intent Investigate the review finding that published R archives still register the retired Azure CDN resolver. Make repository-controlled R installation work with that hostname unavailable, avoid claiming that externally published archives were rewritten, validate local and Databricks-oriented resolution paths, and state the exact external publishing prerequisite for a full artifact migration. ## Linked Sources - Original migration PR: microsoft#2326 - Current migration PR: microsoft#2589 - Maven repository review: microsoft#2589 (comment) - Azure CDN retirement FAQ: https://learn.microsoft.com/en-us/azure/cdn/classic-cdn-retirement-faq - Azure Front Door migration guidance: https://learn.microsoft.com/en-us/azure/cdn/migrate-tier - Apache Spark package repository configuration: https://spark.apache.org/docs/3.5.0/configuration.html#runtime-environment ## Rationale Existing release archives cannot be repaired by a source-only change because their generated sparklyr metadata is already published. Version-matched component downloads plus an explicit Blob resolver and `extensions = character()` provide a tested repository-controlled path without racing or misrepresenting external publication. Future generated archives inherit the corrected resolver from PackageUtils; fully repairing historical metadata still requires an authorized regeneration and publish to the `mmlspark/rrr` container (or a replacement release). Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
ranadeepsingh
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Aug 3, 2026
## Summary Correct the Spark Packages and Python installation snippets so both identify SynapseML 1.0.15 as the compatible release for Spark 3.4 while retaining SynapseML 1.1.3 for Spark 3.5. ## Prompting Intent Address the remaining actionable review feedback on PR microsoft#2589 in the existing branch, verify the surrounding compatibility guidance stays consistent, run targeted website validation and code review, and rerun the full PR checks. ## Linked Sources - Pull request and review feedback: microsoft#2589 - Original migration context: microsoft#2326 ## Rationale The Databricks, Fabric, and SBT guidance already distinguishes SynapseML 1.1.3 for Spark 3.5 from 1.0.15 for Spark 3.4. Updating only the two stale explanatory references restores consistency without changing the Spark 3.5 commands that the snippets demonstrate. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
ranadeepsingh
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Aug 4, 2026
* chore: migrate artifact links off retiring Azure CDN ## Summary Replace all 400 current-master references to mmlspark.azureedge.net with the repository-owned mmlspark Blob Storage origin across runtime package configuration, release output, examples, documentation, notebooks, and every published documentation version. ## Prompting Intent Recreate the intent of the stale CDN-removal PR on current master only after verifying the supported artifact destination and Azure CDN retirement path. Audit each endpoint use by semantics, preserve package and content paths, validate live artifacts and package resolution, and avoid changing or closing the original PR. ## Linked Sources - Original proposal: #2326 - Azure CDN retirement FAQ: https://learn.microsoft.com/en-us/azure/cdn/classic-cdn-retirement-faq - Azure CDN migration guidance: https://learn.microsoft.com/en-us/azure/cdn/migrate-tier - Azure Front Door/CDN comparison: https://learn.microsoft.com/en-us/azure/frontdoor/front-door-cdn-comparison ## Rationale SynapseML's release pipeline publishes artifacts directly to the mmlspark storage account, the repository already uses that public Blob Storage origin extensively, and byte-for-byte URL checks confirmed the CDN currently proxies the same content. Using the verified origin removes the retiring CDN hostname without inventing an unverified Front Door name, while preserving Maven, documentation, R-package, model, dataset, and icon path semantics. Historical links that already return 404 retain the same status and are not broadened into unrelated artifact-repair work. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * docs: make R setup independent of retired CDN ## Summary Repair current and versioned R setup guidance so each release installs its six published, version-matched component archives and resolves SynapseML JVM artifacts through Blob Storage. Document the compatibility bypass required by already-published wrappers, correct the Databricks setup and LightGBM example, remove invalid HTML-page Maven repositories from the Docker demo, and add generator/docs regressions. ## Prompting Intent Investigate the review finding that published R archives still register the retired Azure CDN resolver. Make repository-controlled R installation work with that hostname unavailable, avoid claiming that externally published archives were rewritten, validate local and Databricks-oriented resolution paths, and state the exact external publishing prerequisite for a full artifact migration. ## Linked Sources - Original migration PR: #2326 - Current migration PR: #2589 - Maven repository review: #2589 (comment) - Azure CDN retirement FAQ: https://learn.microsoft.com/en-us/azure/cdn/classic-cdn-retirement-faq - Azure Front Door migration guidance: https://learn.microsoft.com/en-us/azure/cdn/migrate-tier - Apache Spark package repository configuration: https://spark.apache.org/docs/3.5.0/configuration.html#runtime-environment ## Rationale Existing release archives cannot be repaired by a source-only change because their generated sparklyr metadata is already published. Version-matched component downloads plus an explicit Blob resolver and `extensions = character()` provide a tested repository-controlled path without racing or misrepresenting external publication. Future generated archives inherit the corrected resolver from PackageUtils; fully repairing historical metadata still requires an authorized regeneration and publish to the `mmlspark/rrr` container (or a replacement release). Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * docs: correct Spark 3.4 compatibility guidance ## Summary Correct the Spark Packages and Python installation snippets so both identify SynapseML 1.0.15 as the compatible release for Spark 3.4 while retaining SynapseML 1.1.3 for Spark 3.5. ## Prompting Intent Address the remaining actionable review feedback on PR #2589 in the existing branch, verify the surrounding compatibility guidance stays consistent, run targeted website validation and code review, and rerun the full PR checks. ## Linked Sources - Pull request and review feedback: #2589 - Original migration context: #2326 ## Rationale The Databricks, Fabric, and SBT guidance already distinguishes SynapseML 1.1.3 for Spark 3.5 from 1.0.15 for Spark 3.4. Updating only the two stale explanatory references restores consistency without changing the Spark 3.5 commands that the snippets demonstrate. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> --------- Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
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website/docs/documentationfolder.Make sure you choose the correct class
estimators/transformersand namespace.DocTablepoints to correct API link.yarn run startto make sure the website renders correctly.<!--pytest-codeblocks:cont-->before each python code blocks to enable auto-tests for python samples.WebsiteSamplesTestsjob pass in the pipeline.