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Copy file name to clipboardExpand all lines: docs/deployments/batch-api/endpoints.md
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@@ -33,7 +33,7 @@ Submitting data in the request can be useful in the following scenarios:
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* you want to avoid using S3 as an intermediate storage layer
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```yaml
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POST <batch_api_endpoint>/:
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POST <batch_api_endpoint>:
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{
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"workers": <int>, # the number of workers to allocate for this job (required)
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"item_list": {
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If a single S3 file contains a lot of samples/rows, try the next submission strategy.
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```yaml
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POST <batch_api_endpoint>/:
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POST <batch_api_endpoint>:
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{
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"workers": <int>, # the number of workers to allocate for this job (required)
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"file_path_lister": {
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* one or more S3 files contains a large number of samples and must be broken down into batches
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```yaml
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POST <batch_api_endpoint>/:
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POST <batch_api_endpoint>:
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{
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"workers": <int>, # the number of workers to allocate for this job (required)
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"delimited_files": {
@@ -146,7 +146,7 @@ You can get the status of a job by making a GET request to `<batch_api_endpoint>
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See [Job Status Codes](statuses.md) for a list of the possible job statuses and what they mean.
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```yaml
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GET <batch_api_endpoint>/<job_id>:
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GET <batch_api_endpoint>?jobID=<jobID>:
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RESPONSE:
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{
@@ -188,7 +188,7 @@ Stop a job in progress. You can also use the Cortex CLI command
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You stop a running job by making a DELETE request to `<batch_api_endpoint>/<job_id>` (note that you can also delete a job with the Cortex CLI command `cortex delete <api_name> <job_id>`).
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