query slow about near real time data

when send batch query to Realtime processes tasks, the performance is too bad. TPS only have 80, response time is more than one second,
max response time can be 30 second and 99% response time can be 15 second.
what I confused is the data of Realtime processes are in mem, why response time of query is so long?

### Affected Version

v druid-0.16.1-incubating.

### Description

- Cluster size
coordinator and overlord: 2
historical: 7
middleManager: 7
broker: 5

- The testing tool is jmeter
- testing result
thread num: 500
TPS: 107.80
average response time: 4372ms
99% response time: 15559ms
max response time: 30150ms
min response time: 373
- the Flame chart of Realtime task code when test

- the configuration of middleManager

- the configuration of Realtime tasks
```
{
"type": "kafka",
"dataSchema": {
"dataSource": "xxxx",
"parser": {
"type": "string",
"parseSpec": {
"format": "json",
"timestampSpec": {
"column": "timestamp",
"format": "posix"
},
"dimensionsSpec": {
"dimensions": ["tag1","tag2","tag3","tag4","tag5","tag6","tag7"],
"dimensionExclusions": [
"timestamp",
"value"
]
}
}
},
"metricsSpec": [
{
"name": "value",
"fieldName": "value",
"type": "doubleSum"
}
],
"granularitySpec": {
"type": "uniform",
"segmentGranularity": "HOUR",
"queryGranularity": "NONE",
"rollup" : false
}
},
"tuningConfig": {
"type": "kafka",
"intermediatePersistPeriod": "PT1H",
"maxTotalRows": "245000000",
"maxRowsPerSegment": 5000000
},
"ioConfig": {
"topic": "xxxxx",
"consumerProperties": {
"bootstrap.servers": "xxxx:9092"
},
"taskCount": 16,
"replicas": 1,
"taskDuration": "PT1H"
}
}
```

- about segments

- my query
```
{
"queryType": "timeseries",
"dataSource": "xxxx",
"granularity": "second",
"context": {
"skipEmptyBuckets": true,
"vectorize": "true"
},
"filter": { "type": "and", "fields": [{ "type": "selector", "dimension": "endpoint", "value": "host"}, { "type": "selector", "dimension": "metric", "value":"cpu.busy"}] },
"aggregations": [
{ "type": "count", "name": "count"},
{ "type": "stringLast", "name": "dsType", "fieldName": "counterType" },
{ "type": "doubleMax", "name": "max_value", "fieldName": "value" },
{ "type": "doubleMin", "name": "min_value", "fieldName": "value" },
{ "type": "doubleSum", "name": "sum_value", "fieldName": "value" }
],
"postAggregations": [
{ "type": "arithmetic",
"name": "avg",
"fn": "/",
"fields": [
{ "type": "fieldAccess", "name": "sum_value", "fieldName": "sum_value" },
{ "type": "fieldAccess", "name": "count", "fieldName": "count" }
]
}
],
"intervals": [ "2020-05-25T15:35:00+08:00/2020-05-25T15:52:00+08:00" ]
}
```

Start with the supplied JMeter results, realtime task configuration, flame chart, segment screenshots, and timeseries query. Compare query latency with the realtime-task and segment setup to isolate the bottleneck; done would require a confirmed cause and a concrete, reproducible change or recommendation.

Written by the indexing model from the issue text.