要解析JSON，请考虑使用专用的json functions：

SELECT
    toInt32(column_values[1]) AS I2,
    toInt32(column_values[2]) AS I3,
    column_values[3] AS I8
FROM 
(
    SELECT
        arrayJoin(JSONExtract(json, 'DataSets', 'Array(Array(Tuple(Int32, String)))')) AS row,
        arraySort(x -> (x.1), row) AS row_with_sorted_columns,
        arrayMap(x -> (x.2), row_with_sorted_columns) AS column_values
    FROM 
    (
        SELECT '{"AgentID":"10.1.8.1", "Header":{"Version":9,"Count":2}, "DataSets":[\n          [{"I":3,"V":"151"},{"I":8,"V":"109.195.122.130"},{"I":2,"V":"231"}],\n          [{"I":2,"V":"341"},{"I":3,"V":"221"},{"I":8,"V":"109.195.122.233"}]]}' AS json
    )
)

/*
┌─I2──┬─I3──┬─I8──────────────┐
│ 231 │ 151 │ 109.195.122.130 │
│ 341 │ 221 │ 109.195.122.233 │
└─────┴─────┴─────────────────┘
*/

(To获取有关JSON解析的更多信息，请参阅How to extract json from json in clickhouse?）
上面的实现依赖于Datasets-array的固定结构。正如我在真实的世界中所理解的那样，这个结构具有任意模式（https://www.iana.org/assignments/ipfix/ipfix.xhtml），例如：

{
   "AgentID":"192.168.21.15",
   "Header":{},
   "DataSets":[
      [
         {"I":8, "V":"192.16.28.217"},
         {"I":12, "V":"180.10.210.240"},
         {"I":5, "V":2},
         {"I":4, "V":6},
         {"I":7, "V":443},
         {"I":6, "V":"0x10"}
      ]
   ]
}

因此，它出现了一个表与任意列计数的问题。ClickHouse不支持此功能-看看如何可能在这种情况下提出的表https://stackoverflow.com/search?q=%5Bclickhouse%5D+pivot。