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    English

      Data Type

      All Data Types

      Category
      Supported Types Supported by Property
      Numerical int32int64uint32uint64floatdoubledecimal Yes
      Textual stringtext Yes
      Temporal datetimetimestamp Yes
      Spatial point Yes
      Binary blob Yes
      Boolean bool No
      Null null No
      Graph Data NODE、EDGE、PATH No
      List list(with elements of the above types) Yes but only when elements are numerical, textual or temporal except decimal
      Set set(with elements of the above types except list Yes but only when elements are numerical, textual or temporal except decimal
      Object object No
      Tabular TABLE No

      Data Types of Property

      Type
      Description
      int32 4 bytes, with sign
      uint32 4 bytes, no sign
      int64 8 bytes, with sign
      uint64 8 bytes, no sign
      float 4 bytes, 6 significant digits
      double 8 bytes, 15 significant digits
      decimal Precision[1](1~65) and scale[2](0~30) should be specified
      string The default type when creating property, length <= 60,000 bytes
      text No limit on length
      datetime Valid input formats yyyy-mm-dd hh:mm:ss and yyyy-mm-dd hh:mm:ss.ssssss, valid range from '1000-01-01 00:00:00.000000' to '9999-12-31 23:59:59.499999', stored as an uint64
      timestamp Valid input formats are yyyy-mm-dd hh:mm:ss, yyyy-mm-dd, yyyymmddhhmmss and yyyymmdd, stored as an uint32 that equals the number of seconds from '1970-01-01 00:00:00 UTC' onwards, the time zone could be set via RequestConfig of the desired SDK
      point Geographical coordinates or 2D coordinates, where the key value is recorded as double
      blob Binary format of file, image, audio and video, length subject to the max_rpc_msgsize (by default 4M) of the server setting
      list int32[]int64[]uint32[]uint64[]float[]double[]string[]text[]datetime[]timestamp[]
      set set(int32)set(int64)set(uint32)set(uint64)set(float)set(double)set(string)set(text)set(datetime)set(timestamp)

      [1]Precision is the sum of the lengths of integers and decimals, excluding the point
      [2]Scale is the lenght of decimals

      Data Types of RETURN

      Type
      Data Structure
      NODE {id: , uuid: , schema: , values: {...}}
      EDGE {uuid: , schema: , from: , from_uuid: , to: , to_uuid: , values: {...}}
      PATH {length: , nodes: [...], edges: [...]}
      TABLE {name: , headers: [...], rows: [...]}
      ATTR Other than the above four types

      Examples:

      The NODE structure of Alice in the above chart:

      {
      	"id": "STU001",
      	"uuid": 1,
      	"schema": "student",
      	"values": {
      		"name": "Alice",
      		"age": 25
      	}
      }
      

      The EDGE structure in the above chart:

      {
      	"uuid": 53,
      	"schema": "studyAt",
      	"from": "STU001",
      	"to": "UNV001",
      	"from_uuid": 1,
      	"to_uuid": 1001,
      	"values": {
      		"start": 2001,
      		"end": 2005
      	}
      }
      

      The PATH structure representing 'Alice studies at Oxford' in the above chart:

      {
      	"length": 1,
      	"nodes": [{
      		"id": "STU001",
      		"uuid": 1,
      		"schema": "student",
      		"values": {
      			"name": "Alice",
      			"age": 25
      		}
      	}, {
      		"id": "UNV001",
      		"uuid": 1001,
      		"schema": "university",
      		"values": {
      			"name": "Oxford"
      		}
      	}],
      	"edges": [{
      		"uuid": 53,
      		"schema": "studyAt",
      		"from": "STU001",
      		"to": "UNV001",
      		"from_uuid": 1,
      		"to_uuid": 1001,
      		"values": {
      			"start": 2001,
      			"end": 2005
      		}
      	}]
      }
      

      Consider a tabular structure with alias group_stats:

      | group_name | count |
      |------------|-------|
      | green      |   5   |
      | red        |   1   |
      | yellow     |   2   |
      

      The TABLE structure is:

      {
      	"name": "group_stats",
      	"headers": ["group_name", "count"],
      	"rows": [
      		["green", 5],
      		["red", 1],
      		["yellow", 2]
      	]
      }
      

      Regarding how to specify a valid return format in RETURN clause, please read the table at the end of documentation RETURN.

      About NULL

      null is produced when:

      • inserting a new metadata (insert()insert().overwrite()), those properties not provided will be null
      • creating a new property under a schema, this property of those metadata that already exist will be null
      • returning a non-existent property in a RETURN clause, null will be returned
      • no result found for a query (find()khop()、template) that uses prefix OPTIONAL, the metadata returned will be null

      When null participates in a conditional judgement and if:

      • it is sure about the result, then return this result
      • it is NOT sure about the result, then return null
      Expression
      Result
      Explanation
      null == 3 null It's not sure about the result of comparing null with 3, so return null. Same result returns for operators !=, <, >, >=, <=
      null == null null It's not sure. Same result for operators !=, <, >, >=, <=
      [1, null, 2] == [1, 3, 2] null It's not sure. Same result for operator !=
      [1, null, 2] == [1, null, 2] null It's not sure. Same result for operator !=
      [1, null, 2] == [1, null, 3] false It's sure since 2 and 3 are different. Return true for operator !=
      [1, null, 2] == [1, null, 2, 3] false It's sure since lengths of two lists are different. Return true for operator !=
      null <> [1, 3] null It's not sure. Same result for operator <=>
      1 IN [1, null, 2] true It's sure since 1 does exist in the list. Returns false for operator NOT IN
      3 IN [1, null, 2] null It's not sure. Same result for operator NOT IN
      null IN [ ] false It's sure since the list is empty. Returns true for operator NOT IN

      Any numerical computation (+, -, *, /, %) participated by null will return null.

      Any aggregation operation (count(), sum(), max(), min(), avg(), stddev(), collect()) participated by null will ignore the rows with null.

      Regarding functions and operators related with null please read documentations coalesce()ifnull()IS NULLIS NOT NULL.

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