![]() If you have a large amount of update traffic, Takes each document to become searchable. Sending a large volume of single-document batches can increase the amount of time it Although the index is automatically rebuilt periodically, to scale down as quickly as possible you can explicitly run indexing when you are done deleting documents. If your domain has scaled up to accommodate your index size and you delete a large number of documents, the domain scales down the next time the full index is rebuilt. Amazon CloudSearch Domain Not Scaling Down After Deleting Documents You can use a validation tool such as the JSON Validator or W3C Markup Validation Service to identify invalid characters.ĭeleting All Documents in an Amazon CloudSearch DomainĪmazon CloudSearch currently does not provide a mechanism for deleting all of the documents in a domain. Both JSON and XML batches can contain only UTF-8 characters that are valid in XML. Multi-valued fields must contain at least one value.īad characters-one problem that can be difficult to detect if you do not filter your data while generating your document batch is that can contain characters that are invalid in XML. Multi-valued fields without a value-when specifying document data in JSON, you cannot specify an empty array as the value of a field. ![]() Document IDs must be at least 1 and no more than 128 characters long. ![]() For more information about formatting your data, see Creating Document Batches.ĭocument IDs with bad values-A document ID can contain any letter or number and the following characters: _ - = # : / ? &. Delete operations only need to specify the type and ID. For add operations, make sure that the type, ID, and at least one field are specified for each document. If it is, check for invalid document IDs and make sure you have specified the operation type for each document. Similarly, if you attempt to configure a domain from an invalid batch, Amazon CloudSearch responds with the content and meta-data fields instead of the fields in the batch.įirst, make sure that the batch is valid XML or JSON. Since these are not normally the fields configured for the domain, you get errors stating that the fields don't exist. Not Recognized as a Document Batch-if Amazon CloudSearch doesn’t recognize your data as a valid document batch when you upload data using the console, Amazon CloudSearch generates a valid batch that contains a single content field and generic metadata fields such as content_encoding, content_type, and resourcename. To identify any problems, run your document batch through a validation tool such as the W3C Markup Validation Service. You are especially likely to encounter issues if your fields contain XML data-the data must be XML-encoded or enclosed in CDATA sections. Invalid XML-document batches must be well-formed XML. This will identify any fundamental issues with the data. To do that, run it through a validation tool such as the JSON Validator. Invalid JSON-if you are using JSON, the first thing to do is make sure there are no JSON syntax errors in your document batch. Some common problems and their solutions: When you attempt to upload it or use it to configure fields for your domain. If your document data is not formatted correctly or contains invalid values, you will get errors Inconsistent Results When Using Cursors for Deep Paging.Using Wildcards to Search Text Fields Doesn't Produce Expected Results.Amazon CloudSearch Console Permissions Errors. ![]()
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