meta tag feature sample tests

* Spinning up MT cluster which consists of 4 shard groups, 2 MTs per shard.
  Each read MT has 10G Mem and 2 CPU cores on GKE n1-highmem-2 nodes.
* Feeding it with a fakemetrics generator. In total it generates 5 million metrics,
  each metric has 12 tags:
  8 of them have the same tags and values for all metrics.
  3 of them have a unique value for each metric
  1 is a tag of the format "host=[0-9]+"
    in total there are 30k possible values for this tag then they start to repeat,
    so each possible value such as "host=123" has 5M/30k = 166 metrics associated.
* 30k Meta records get generated. Each of the records is associated with one "host=X"
  tag/value, so there are 166 metrics per meta record.
* Each meta record has 3 meta tags:
  1 is of the format "datacenter=dc[0-2]" and there are only 3 possible values. So each
    key/value combination corresponds to 30k/3 = 10k metrics
  1 has only a single tag/value "stage=prod"
  1 has two possible values which are "operatingSystem=windows" and "operatingSystem=redhat",
    66% of the meta records get redhat, 33% get windows
* Waiting until all Metrictank instances have loaded all the meta records
* Submitting queries and timing them:

### test 1: querying single metric to test if result has been enriched with meta tags correctly

time curl -s -H 'X-Org-Id: 1' 'http://localhost:6060/render?target=seriesByTag("region=west99003")&maxDataPoints=1' | jq
real    0m 0.02s
user    0m 0.00s
sys     0m 0.00s
[
  {
    "target": "some.id.of.a.metric.99003;afewmoretags=forgoodmeasure;anothertag=somelongervalue;datacenter=dc3;goodforpeoplewhojustusetags=forbasicallyeverything;host=9002;lotsandlotsoftags=morefunforeveryone;manymoreother=lotsoftagstointern;onetwothreefourfivesix=seveneightnineten;operatingSystem=redhat;os=ubuntu;region=west99003;secondkey=anothervalue99003;stage=prod;thirdkey=onemorevalue99003",
    "tags": {
      "stage": "prod",
      "datacenter": "dc3",
      "lotsandlotsoftags": "morefunforeveryone",
      "operatingSystem": "redhat",
      "afewmoretags": "forgoodmeasure",
      "anothertag": "somelongervalue",
      "thirdkey": "onemorevalue99003",
      "goodforpeoplewhojustusetags": "forbasicallyeverything",
      "name": "some.id.of.a.metric.99003",
      "os": "ubuntu",
      "region": "west99003",
      "secondkey": "anothervalue99003",
      "host": "9002",
      "manymoreother": "lotsoftagstointern",
      "onetwothreefourfivesix": "seveneightnineten"
    },
    "datapoints": [
      [
        88686.84348296668,
        1574128200
      ]
    ]
  }
]

### test 2: querying region (metric tag) by prefix and then filtering result set by dc (meta tag)

/ # time curl -s -H 'X-Org-Id: 1' 'http://localhost:6060/render?target=countSeries(seriesByTag("region^=west49999"))&maxDataPoints=1' | jq
real    0m 0.51s
user    0m 0.00s
sys     0m 0.00s
[
  {
    "target": "countSeries(seriesByTag(\"region^=west49999\"))",
    "tags": {
      "name": "countSeries(seriesByTag(\"region^=west49999\"))"
    },
    "datapoints": [
      [
        110,
        1574128200
      ]
    ]
  }
]
/ # time curl -s -H 'X-Org-Id: 1' 'http://localhost:6060/render?target=countSeries(seriesByTag("datacenter=dc2","region^=west49999"))&maxDataPoints=1' | jq
real    0m 0.70s
user    0m 0.00s
sys     0m 0.00s
[
  {
    "target": "countSeries(seriesByTag(\"datacenter=dc2\",\"region^=west49999\"))",
    "tags": {
      "name": "countSeries(seriesByTag(\"datacenter=dc2\",\"region^=west49999\"))"
    },
    "datapoints": [
      [
        36,
        1574128300
      ]
    ]
  }
]


### test 3: querying large result set via metric tag, then filtering result set by a meta tag that matches all metrics (heavy query)

/ # time curl -s -H 'X-Org-Id: 1' 'http://localhost:6060/render?target=countSeries(seriesByTag("secondkey^=anothervalue1234"))&maxDataPoints=1' | jq
real    0m 1.71s
user    0m 0.00s
sys     0m 0.00s
[
  {
    "target": "countSeries(seriesByTag(\"secondkey^=anothervalue1234\"))",
    "tags": {
      "name": "countSeries(seriesByTag(\"secondkey^=anothervalue1234\"))"
    },
    "datapoints": [
      [
        1096,
        1574128400
      ]
    ]
  }
]
/ # time curl -s -H 'X-Org-Id: 1' 'http://localhost:6060/render?target=countSeries(seriesByTag("secondkey^=anothervalue1234","stage=prod"))&maxDataPoints=1' | jq
real    0m 8.61s
user    0m 0.00s
sys     0m 0.00s
[
  {
    "target": "countSeries(seriesByTag(\"secondkey^=anothervalue1234\",\"stage=prod\"))",
    "tags": {
      "name": "countSeries(seriesByTag(\"secondkey^=anothervalue1234\",\"stage=prod\"))"
    },
    "datapoints": [
      [
        1096,
        1574128400
      ]
    ]
  }
]


### test 4: query which involves 2 metric tags and 2 meta tags

/ # time curl -s -H 'X-Org-Id: 1' 'http://localhost:6060/render?target=countSeries(seriesByTag("host^=1111","afewmoretags=~forgoodmeasure","datacenter=dc2","stage=prod"))&maxDataPoints=1' | jq
real    0m 5.95s
user    0m 0.00s
sys     0m 0.00s
[
  {
    "target": "countSeries(seriesByTag(\"host^=1111\",\"afewmoretags=~forgoodmeasure\",\"datacenter=dc2\",\"stage=prod\"))",
    "tags": {
      "name": "countSeries(seriesByTag(\"host^=1111\",\"afewmoretags=~forgoodmeasure\",\"datacenter=dc2\",\"stage=prod\"))"
    },
    "datapoints": [
      [
        819,
        1574128900
      ]
    ]
  }
]