Azure blob storage zip and download multple files

Then, use the azcopy copy command with the --list-of-versions option. You can download a blob snapshot by referencing the DateTime value of a blob snapshot. For a complete list, see options. Skip to main content. This browser is no longer supported. Download Microsoft Edge More info. Contents Exit focus mode. Please rate your experience Yes No.

Any additional feedback? Tip This example encloses path arguments with single quotes ''. Note If the Content-md5 property value of a blob contains a hash, AzCopy calculates an MD5 hash for downloaded data and verifies that the MD5 hash stored in the blob's Content-md5 property matches the calculated hash.

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No surprises here really, the more CPU we have, the less is the difference between 1 and 5 concurrent requests. One thing to note here though is the difference between Standard and Premium storage, Premium storage significally lowers the processing time. This numbers has been taken from the Azure Portal so they are kinda rough. We can see that both S1 and S2 are quite close to maxing out the CPU when processing 5 concurrent requests. Here we can see that the memory usage is stable throughout, it doesn't matter if we process 1 or 5 requests, the consumption is roughly the same.

You can control which blobs are indexed, and which are skipped, by the blob's file type or by setting properties on the blob themselves, causing the indexer to skip over them. Use indexedFileNameExtensions to provide a comma-separated list of file extensions to index with a leading dot.

For example, to index only the. PDF and. DOCX blobs, do this:. Use excludedFileNameExtensions to provide a comma-separated list of file extensions to skip again, with a leading dot. For example, to index all blobs except those with the. PNG and. JPEG extensions, do this:. If the same file extension is in both lists, it will be excluded from indexing.

The indexer configuration parameters apply to all blobs in the container or folder. Sometimes, you want to control how individual blobs are indexed. You can do this by adding the following metadata properties and values to blobs in Blob storage. When the indexer encounters this properties, it will skip the blob or its content in the indexing run.

Indexing blobs can be a time-consuming process. In cases where you have millions of blobs to index, you can speed up indexing by partitioning your data and using multiple indexers to process the data in parallel. Here's how you can set this up:. Set up several data sources, one per container or folder.

To point to a blob folder, use the query parameter:. Create a corresponding indexer for each data source. All of the indexers should point to the same target search index. One search unit in your service can run one indexer at any given time.

Creating multiple indexers as described above is only useful if they actually run in parallel. To run multiple indexers in parallel, scale out your search service by creating an appropriate number of partitions and replicas.

For example, if your search service has 6 search units for example, 2 partitions x 3 replicas , then 6 indexers can run simultaneously, resulting in a six-fold increase in the indexing throughput. To learn more about scaling and capacity planning, see Adjust the capacity of an Azure Cognitive Search service. Errors that commonly occur during indexing include unsupported content types, missing content, or oversized blobs.

By default, the blob indexer stops as soon as it encounters a blob with an unsupported content type for example, an image. You could use the excludedFileNameExtensions parameter to skip certain content types. However, you might want to indexing to proceed even if errors occur, and then debug individual documents later. For more information about indexer errors, see Indexer troubleshooting guidance and Indexer errors and warnings. There are four indexer properties that control the indexer's response when errors occur.

The following examples show how to set these properties in the indexer definition.