ES5.6.4中数值类型的term查询类型应该是TermQuery还是PointRangeQuery

      最近拜读吴大神之前的一篇文章number?keyword?傻傻分不清楚，文章详细解析了数值类型在Lucene6.0中的查询和存储，包括term查询和range查询。其中有一节分析数值类型term查询慢的原因，提到数值型字段的TermQuery被转换为了PointRangeQuery。我在自己的环境做了一个简单的测试并远程DEBUG，发现没有出现PointRangeQuery类型的查询。不知道是我理解错误还是测试用例有问题。
测试用例：

{

  "from": 0,

  "size": 10,

  "profile": true,

  "query": {

    "bool": {

      "filter": [

        {

          "terms": {

            "rowKey": [

              "201803023990375518829f2c15a01214647835"

            ]

, "boost": 1.0

          }

        }, {

          "terms": {

            "msg_type": [

              2,

              3

            ]

, "boost": 1.0

          }

        }

      ],

      "disable_coord": false,

      "adjust_pure_negative": true,

      "boost": 1

    }

  }

}

 
 其中rowKey为String类型，  msg_type为integer类型。
 
 
profile查询结果：

{

	"id": "[ZBP_rofAShe6QkHoxIO0ow][hik_mac_index_info-2018030100-2018030200][0]",

	"searches": [{

		"query": [{

			"type": "BooleanQuery",

			"description": "#ConstantScore(rowKey:201803023990375518829f2c15a01214647835) #msg_type:{1 3}",

			"time": "26.50874300ms",

			"time_in_nanos": 26508743,

			"breakdown": {

				"score": 115,

				"build_scorer_count": 2,

				"match_count": 0,

				"create_weight": 55373,

				"next_doc": 3294,

				"match": 0,

				"create_weight_count": 1,

				"next_doc_count": 2,

				"score_count": 1,

				"build_scorer": 26449955,

				"advance": 0,

				"advance_count": 0

			},

			"children": [{

				"type": "ConstantScoreQuery",

				"description": "ConstantScore(rowKey:201803023990375518829f2c15a01214647835)",

				"time": "0.2549140000ms",

				"time_in_nanos": 254914,

				"breakdown": {

					"score": 0,

					"build_scorer_count": 4,

					"match_count": 0,

					"create_weight": 27506,

					"next_doc": 1703,

					"match": 0,

					"create_weight_count": 1,

					"next_doc_count": 2,

					"score_count": 0,

					"build_scorer": 225698,

					"advance": 0,

					"advance_count": 0

				},

				"children": [{

					"type": "TermQuery",

					"description": "rowKey:201803023990375518829f2c15a01214647835",

					"time": "0.1888600000ms",

					"time_in_nanos": 188860,

					"breakdown": {

						"score": 0,

						"build_scorer_count": 4,

						"match_count": 0,

						"create_weight": 16734,

						"next_doc": 1200,

						"match": 0,

						"create_weight_count": 1,

						"next_doc_count": 2,

						"score_count": 0,

						"build_scorer": 170919,

						"advance": 0,

						"advance_count": 0

					}

				}]

			},

			{

				"type": "",

				"description": "msg_type:{1 3}",

				"time": "26.11104000ms",

				"time_in_nanos": 26111040,

				"breakdown": {

					"score": 0,

					"build_scorer_count": 4,

					"match_count": 0,

					"create_weight": 2930,

					"next_doc": 0,

					"match": 0,

					"create_weight_count": 1,

					"next_doc_count": 0,

					"score_count": 0,

					"build_scorer": 26107594,

					"advance": 509,

					"advance_count": 2

				}

			}]

		}],

		"rewrite_time": 121798,

		"collector": [{

			"name": "CancellableCollector",

			"reason": "search_cancelled",

			"time": "0.02026900000ms",

			"time_in_nanos": 20269,

			"children": [{

				"name": "SimpleTopScoreDocCollector",

				"reason": "search_top_hits",

				"time": "0.01027800000ms",

				"time_in_nanos": 10278

			}]

		}]

	}],

	"aggregations": []

}

可以看到rowKey字段的查询类型是TermQuery，但是msg_type并没有说明是什么类型，而且通过DEBUG并没有走PointRangeQuery的相关代码，只走了TermQuery。所以感到疑惑，而且msg_type字段的build_scorer的时间确实比较长。
希望大神们能给指点一下。