Table incompatible when using Amazon Glue with Athena in Amazon QuickSight - Amazon QuickSight
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Table incompatible when using Amazon Glue with Athena in Amazon QuickSight

If you are getting errors when using Amazon Glue tables in Athena with Amazon QuickSight, it might be because you're missing some metadata. Follow these steps to find out if your tables don't have the TableType attribute that Amazon QuickSight needs for the Athena connector to work. Usually, the metadata for these tables wasn't migrated to the Amazon Glue Data Catalog. For more information, see Upgrading to the Amazon Glue Data Catalog Step-by-Step in the Amazon Glue Developer Guide.

If you don't want to migrate to the Amazon Glue Data Catalog at this time, you have two options. You can recreate each Amazon Glue table through the Amazon Glue Management Console. Or you can use the Amazon CLI scripts listed in the following procedure to identify and update tables with missing TableType attributes.

If you prefer to use the CLI to do this, use the following procedure to help you design your scripts.

To use the CLI to design scripts
  1. Use the CLI to learn which Amazon Glue tables have no TableType attributes.

    aws glue get-tables --database-name <your_datebase_name>;

    For example, you can run the following command in the CLI.

    aws glue get-table --database-name "test_database" --name "table_missing_table_type"

    Following is a sample of what the output looks like. You can see that the table "table_missing_table_type" doesn't have the TableType attribute declared.

    { "TableList": [ { "Retention": 0, "UpdateTime": 1522368588.0, "PartitionKeys": [ { "Name": "year", "Type": "string" }, { "Name": "month", "Type": "string" }, { "Name": "day", "Type": "string" } ], "LastAccessTime": 1513804142.0, "Owner": "owner", "Name": "table_missing_table_type", "Parameters": { "delimiter": ",", "compressionType": "none", "skip.header.line.count": "1", "sizeKey": "75", "averageRecordSize": "7", "classification": "csv", "objectCount": "1", "typeOfData": "file", "CrawlerSchemaDeserializerVersion": "1.0", "CrawlerSchemaSerializerVersion": "1.0", "UPDATED_BY_CRAWLER": "crawl_date_table", "recordCount": "9", "columnsOrdered": "true" }, "StorageDescriptor": { "OutputFormat": "org.apache.hadoop.hive.ql.io.HiveIgnoreKeyTextOutputFormat", "SortColumns": [], "StoredAsSubDirectories": false, "Columns": [ { "Name": "col1", "Type": "string" }, { "Name": "col2", "Type": "bigint" } ], "Location": "s3://myAthenatest/test_dataset/", "NumberOfBuckets": -1, "Parameters": { "delimiter": ",", "compressionType": "none", "skip.header.line.count": "1", "columnsOrdered": "true", "sizeKey": "75", "averageRecordSize": "7", "classification": "csv", "objectCount": "1", "typeOfData": "file", "CrawlerSchemaDeserializerVersion": "1.0", "CrawlerSchemaSerializerVersion": "1.0", "UPDATED_BY_CRAWLER": "crawl_date_table", "recordCount": "9" }, "Compressed": false, "BucketColumns": [], "InputFormat": "org.apache.hadoop.mapred.TextInputFormat", "SerdeInfo": { "Parameters": { "field.delim": "," }, "SerializationLibrary": "org.apache.hadoop.hive.serde2.lazy.LazySimpleSerDe" } } } ] }
  2. Edit the table definition in your editor to add "TableType": "EXTERNAL_TABLE" to the table definition, as shown in the following example.

    { "Table": { "Retention": 0, "TableType": "EXTERNAL_TABLE", "PartitionKeys": [ { "Name": "year", "Type": "string" }, { "Name": "month", "Type": "string" }, { "Name": "day", "Type": "string" } ], "UpdateTime": 1522368588.0, "Name": "table_missing_table_type", "StorageDescriptor": { "BucketColumns": [], "SortColumns": [], "StoredAsSubDirectories": false, "OutputFormat": "org.apache.hadoop.hive.ql.io.HiveIgnoreKeyTextOutputFormat", "SerdeInfo": { "SerializationLibrary": "org.apache.hadoop.hive.serde2.lazy.LazySimpleSerDe", "Parameters": { "field.delim": "," } }, "Parameters": { "classification": "csv", "CrawlerSchemaSerializerVersion": "1.0", "UPDATED_BY_CRAWLER": "crawl_date_table", "columnsOrdered": "true", "averageRecordSize": "7", "objectCount": "1", "sizeKey": "75", "delimiter": ",", "compressionType": "none", "recordCount": "9", "CrawlerSchemaDeserializerVersion": "1.0", "typeOfData": "file", "skip.header.line.count": "1" }, "Columns": [ { "Name": "col1", "Type": "string" }, { "Name": "col2", "Type": "bigint" } ], "Compressed": false, "InputFormat": "org.apache.hadoop.mapred.TextInputFormat", "NumberOfBuckets": -1, "Location": "s3://myAthenatest/test_date_part/" }, "Owner": "owner", "Parameters": { "classification": "csv", "CrawlerSchemaSerializerVersion": "1.0", "UPDATED_BY_CRAWLER": "crawl_date_table", "columnsOrdered": "true", "averageRecordSize": "7", "objectCount": "1", "sizeKey": "75", "delimiter": ",", "compressionType": "none", "recordCount": "9", "CrawlerSchemaDeserializerVersion": "1.0", "typeOfData": "file", "skip.header.line.count": "1" }, "LastAccessTime": 1513804142.0 } }
  3. You can adapt the following script to update the table input, so that it includes the TableType attribute.

    aws glue update-table --database-name <your_datebase_name> --table-input <updated_table_input>

    The following shows an example.

    aws glue update-table --database-name test_database --table-input ' { "Retention": 0, "TableType": "EXTERNAL_TABLE", "PartitionKeys": [ { "Name": "year", "Type": "string" }, { "Name": "month", "Type": "string" }, { "Name": "day", "Type": "string" } ], "Name": "table_missing_table_type", "StorageDescriptor": { "BucketColumns": [], "SortColumns": [], "StoredAsSubDirectories": false, "OutputFormat": "org.apache.hadoop.hive.ql.io.HiveIgnoreKeyTextOutputFormat", "SerdeInfo": { "SerializationLibrary": "org.apache.hadoop.hive.serde2.lazy.LazySimpleSerDe", "Parameters": { "field.delim": "," } }, "Parameters": { "classification": "csv", "CrawlerSchemaSerializerVersion": "1.0", "UPDATED_BY_CRAWLER": "crawl_date_table", "columnsOrdered": "true", "averageRecordSize": "7", "objectCount": "1", "sizeKey": "75", "delimiter": ",", "compressionType": "none", "recordCount": "9", "CrawlerSchemaDeserializerVersion": "1.0", "typeOfData": "file", "skip.header.line.count": "1" }, "Columns": [ { "Name": "col1", "Type": "string" }, { "Name": "col2", "Type": "bigint" } ], "Compressed": false, "InputFormat": "org.apache.hadoop.mapred.TextInputFormat", "NumberOfBuckets": -1, "Location": "s3://myAthenatest/test_date_part/" }, "Owner": "owner", "Parameters": { "classification": "csv", "CrawlerSchemaSerializerVersion": "1.0", "UPDATED_BY_CRAWLER": "crawl_date_table", "columnsOrdered": "true", "averageRecordSize": "7", "objectCount": "1", "sizeKey": "75", "delimiter": ",", "compressionType": "none", "recordCount": "9", "CrawlerSchemaDeserializerVersion": "1.0", "typeOfData": "file", "skip.header.line.count": "1" }, "LastAccessTime": 1513804142.0 }'