JSON format - Amazon CloudWatch
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JSON format

In a CloudWatch metric stream that uses the JSON format, each Kinesis Data Firehose record contains multiple JSON objects separated by a newline character (\n). Each object includes a single data point of a single metric.

The JSON format that is used is fully compatible with Amazon Glue and with Amazon Athena. If you have a Kinesis Data Firehose delivery stream and an Amazon Glue table formatted correctly, the format can be automatically transformed into Parquet format or Optimized Row Columnar (ORC) format before being stored in S3. For more information about transforming the format, see Converting Your Input Record Format in Kinesis Data Firehose. For more information about the correct format for Amazon Glue, see Which Amazon Glue schema should I use for JSON output format?.

In the JSON format, the valid values for unit are the same as for the value of unit in the MetricDatum API structure. For more information, see MetricDatum. The value for the timestamp field is in epoch milliseconds, such as 1616004674229.

The following is an example of the format. In this example, the JSON is formatted for easy reading, but in practice the whole format is on a single line.

{ "metric_stream_name": "MyMetricStream", "account_id": "1234567890", "region": "us-east-1", "namespace": "AWS/EC2", "metric_name": "DiskWriteOps", "dimensions": { "InstanceId": "i-123456789012" }, "timestamp": 1611929698000, "value": { "count": 3.0, "sum": 20.0, "max": 18.0, "min": 0.0, "p99": 17.56, "p99.9": 17.8764, "TM(25%:75%)": 16.43 }, "unit": "Seconds" }

Which Amazon Glue schema should I use for JSON output format?

The following is an example of a JSON representation of the StorageDescriptor for an Amazon Glue table, which would then be used by Kinesis Data Firehose. For more information about StorageDescriptor, see StorageDescriptor.

{ "Columns": [ { "Name": "metric_stream_name", "Type": "string" }, { "Name": "account_id", "Type": "string" }, { "Name": "region", "Type": "string" }, { "Name": "namespace", "Type": "string" }, { "Name": "metric_name", "Type": "string" }, { "Name": "timestamp", "Type": "timestamp" }, { "Name": "dimensions", "Type": "map<string,string>" }, { "Name": "value", "Type": "struct<min:double,max:double,count:double,sum:double,p99:double,p99.9:double>" }, { "Name": "unit", "Type": "string" } ], "Location": "s3://my-s3-bucket/", "InputFormat": "org.apache.hadoop.mapred.TextInputFormat", "OutputFormat": "org.apache.hadoop.hive.ql.io.HiveIgnoreKeyTextOutputFormat", "SerdeInfo": { "SerializationLibrary": "org.apache.hive.hcatalog.data.JsonSerDe" }, "Parameters": { "classification": "json" } }

The preceding example is for data written on Amazon S3 in JSON format. Replace the values in the following fields with the indicated values to store the data in Parquet format or Optimized Row Columnar (ORC) format.

  • Parquet:

    • inputFormat: org.apache.hadoop.hive.ql.io.parquet.MapredParquetInputFormat

    • outputFormat: org.apache.hadoop.hive.ql.io.parquet.MapredParquetOutputFormat

    • SerDeInfo.serializationLib: org.apache.hadoop.hive.ql.io.parquet.serde.ParquetHiveSerDe

    • parameters.classification: parquet

  • ORC:

    • inputFormat: org.apache.hadoop.hive.ql.io.orc.OrcInputFormat

    • outputFormat: org.apache.hadoop.hive.ql.io.orc.OrcOutputFormat

    • SerDeInfo.serializationLib: org.apache.hadoop.hive.ql.io.orc.OrcSerde

    • parameters.classification: orc