The longest official place name in Australia

Guestbook

Mamungkukumpurangkuntjunya Hill, is a hill in South Australia. The name means “where the devil urinates” in the regional Pitjantjatjara language. The name is the longest official place name in Australia. The hill is located approximately 108.8 km west north-west of Marla.

Mamungkukumpurangkuntjunya Hill

House Prices Down Under

Guestbook

A look at historical house prices in Sydney and Melbourne from 1880 to 2010.

Historical house prices in Sydney and Melbourne from 1880 to 2010

Melbourne Median vs Average Wage 1965 - 2010.

Melbourne Median vs Average Wage 1965 - 2010

It must be remembered that house prices are determined by the demand and supply of credit, not the demand for and supply of housing.

房价不与国民收入，社会福利放在一起进行讨论，无异于光天化日里耍流氓。

AlphaGo movie

Guestbook

AlphaGo is an intriguing movie, full of striking imagery.

Proud of witnessing DeepMind and Google are making history …

AlphaGo movie

AlphaGo movie

AlphaGo movie

AlphaGo movie

AlphaGo movie

AlphaGo movie

AlphaGo movie

AlphaGo movie

AlphaGo movie

AlphaGo movie

AlphaGo movie

AlphaGo movie

AlphaGo movie

AlphaGo movie

AlphaGo movie

AlphaGo movie

AlphaGo movie

AlphaGo movie

AlphaGo movie

AlphaGo movie

AlphaGo movie

AlphaGo movie

AlphaGo movie

AlphaGo movie

AlphaGo movie

AlphaGo movie

AlphaGo movie

AlphaGo movie

AlphaGo movie

AlphaGo movie

AlphaGo movie

RESTful calls to create Index and Mappings in ElasticSearch

Guestbook

There is a simple way, using RESTful client to create Index and Mappings in ElasticSearch, for example, with ElasticSearch Head plugin.

Create Index in ElasticSearch with Settings JSON file. URL: http://localhost:9200/orders/, Method: PUT

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
{
  "settings": {
    "index": {
      "number_of_shards": 1,
      "number_of_replicas": 0,
      "analysis": {
        "filter": {
          "partial_matching_filter": {
            "type": "edge_ngram",
            "min_gram": 1,
            "max_gram": 40
          }
        },
        "normalizer": {
           "lowercase_normalizer": {
             "type": "custom",
             "filter": ["lowercase"]
           }
         },        
        "analyzer": {
          "partial_matcher": {
            "type": "custom",
            "tokenizer": "standard",
            "filter": [
              "lowercase",
              "partial_matching_filter"
            ]
          }
        }
      }
    }
  }
}

Create Mappings in ElasticSearch with Mappings JSON file. URL: http://localhost:9200/orders/_mapping/order, Method: PUT

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
{
  "dynamic": "false",
  "_all": { "enabled": false},
  "properties": {
    "customer_id": {
      "type": "keyword"
    },
    "encryption_key_id": {
      "type": "keyword",
      "index": "false"
    },
    "metadata_tags": {
      "type": "text",
      "analyzer": "whitespace"
    },
    "category": {
      "type": "keyword"
    },
    "order_creation_date": {
      "type": "date",
      "format": "date_optional_time"
    },
    "order_reference": {
      "type": "text"
    },
    "order_id": {
      "type": "keyword",
      "normalizer": "lowercase_normalizer"
    },
    "to_name": {
      "type": "text",
      "analyzer": "partial_matcher",
      "search_analyzer": "standard"
    },
    "to_suburb": {
      "type": "text",
      "analyzer": "whitespace"
    },
    "to_state": {
      "type": "text",
      "analyzer": "whitespace"
    },
    "to_postcode": {
      "type": "text",
      "analyzer": "whitespace"
    },
    "to_email": {
      "type": "text",
      "analyzer": "whitespace"
    }
  }
}

To add a new fields to ElasticSearch, while dynamic mapping is off:

1
2
3
{
  "dynamic": "false"
}

Run with additional fields JSON file, with URL: http://localhost:9200/orders/_mapping/order, Method: PUT

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
{
  "properties": {
    "from_name": {
      "type": "text",
      "analyzer": "partial_matcher",
      "search_analyzer": "standard"
    },
    "from_business_name": {
      "type": "text",
      "analyzer": "partial_matcher",
      "search_analyzer": "standard"
    },
    "from_suburb": {
      "type": "text",
      "analyzer": "whitespace"
    },
    "from_state": {
      "type": "text",
      "analyzer": "whitespace"
    },
    "from_postcode": {
      "type": "text",
      "analyzer": "whitespace"
    },
    "from_country": {
      "type": "text",
      "analyzer": "whitespace"
    },
    "from_email": {
      "type": "text",
      "analyzer": "whitespace"
    },
    "from_phone": {
      "type": "text",
      "analyzer": "whitespace"
    }
  }
}

An ElasticSearch query example, with URL: http://localhost:9200/orders/_search, Method: POST

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
{
 "query": {
   "bool": {
     "must": [
       {"match": {"customer_id": "1234567890"} },
       {"simple_query_string": {
            "query": "unlabelled+unmanifested",
            "fields": ["metadata_tags"]
       } },
       {
         "bool": {
           "should": [
             {
               "multi_match": {
                 "query": "TerrenceMiao",
                 "fields": [
                   "name", "business_name", "order_id", "shipment_id", "sender_references", "article_ids"
                 ]
               }
             },
             {"match": {"phone": "abracadbravvv5/vv70qBu+/ve+/ve6EuA7vv70g77+9Su+/ve+/vX5y77+95JuV"} },
             {
               "multi_match": {
                 "query": "gdgdggddvvv75/vv70qBu+/ve+/ve6EuA7vv70g77+9Su+/ve+/vX5y77+95JuV",
                 "fields": [
                   "suburb", "state", "country", "postcode", "email"
                 ]
               }
             }
           ]
         }
       },
       {"simple_query_string": {
         "query": "DESPATCH",
         "fields": ["movement_type"]
       } }
     ]
   }
 },
 "sort": [
   {"order_creation_date": {"order": "desc", "unmapped_type": "date"} },
   {"shipment_creation_date": {"order": "desc"} }
 ],
 "from": "0","size": "1"
}

An example query with date/time type in a range:

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
{
  "query": {
    "range": {
      "shipment_creation_date": {
        "gte": "2018-04-19T15:30:00",
        "lte": "now",
        "time_zone": "+10:00"

      }
    }
  },
  "from": 0,
  "size": 10,
  "sort": [],
  "aggs": {}
}