BigQuery example use
select d.message.reqPath, CAST(d.netPerf.downloadTime AS INT64) * 1 As dtime FROM `akamai-206503.datastream_logs.edgescapedemo` , UNNEST(data) as d where d.message.reqPath LIKE "%.ts" or d.message.reqPath LIKE "%.m3u8" order by dTime desc
You easily point out the files that take longer to download. Then, you can investigate further and make specific queries about the title, allowing the customer to identify the root cause of the problem.
Using an aggregate stream, you can also find out if the numbers of errors have increased. Aggregate data streams retrieve real-time of 4xx and 5xx HTTP error occurrences.
http --auth-type edgegrid -a datastream-pull-api: ":/datastream-pull-api/v1/streams/1201/aggregate-logs?start=2019-02-15T09:19:37Z&end=2019-02-17T10:40:00Z&aggregateMetric=2xx%2C3xx%2C4xx%2C5xx&page=0&size=100"
You can then ingest the return JSON file into BigQuery and visualize the errors in time.