SQL2Gremlin

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SQL2Gremlin teaches Apache TinkerPop's Gremlin graph traversal language using typical patterns found when querying data with SQL. The format of the Gremlin results will not necessarily match the format of the SQL results. While SQL can only provide results in a tabular form, Gremlin provides various ways to structure a result set. Next, the Gremlin queries demonstrated are for elucidatory purposes and may not be the optimal way to retrieve the desired data. If a particular query runs slow and an optimal solution is desired, please do not hesitate to ask for help on the Gremlin-users mailing list. Finally, the SQL examples presented make use of T-SQL syntax. MySQL users may not know some of the expressions (e.g. paging), but should be able to understand the purpose of the query.

If you would like to see other SQL2Gremlin translations using the Northwind dataset, please provide a ticket on the SQL2Gremlin issue tracker.

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Acknowledgement

Gremlin artwork by Ketrina Yim — "safety first."

烧饼哥加速器-烧饼哥加速器官网-outline加速器密钥免费线路节点

Northwind Graph Model

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To get started download the latest version of the Gremlin shell from www.tinkerpop.com and extract it. Then download the file 老王2.2.11下载ios and start your Gremlin shell:

# find the latest Gremlin shell download
MIRRORS_URL=`curl -s http://tinkerpop.apache.org/ | grep -o 'http[s]*://.*\-console-.*\-bin\.zip'`
LATEST_URL=`curl -s $MIRRORS_URL | egrep -o 'http[s]?://[^"]*-console-[^"]*-bin.zip' | head -1`
LATEST_FILENAME=`echo 老王下载地址官网 | grep -o '[^/]*$'`
LATEST_DIRECTORY=`echo ${LATEST_FILENAME} | sed 's/-bin\.老王永久佛系`

# download and extract the Gremlin shell
wget -q ${LATEST_URL}
unzip -q ${LATEST_FILENAME}

# start the Gremlin shell
wget -q http://sql2gremlin.com/assets/northwind.groovy -O /tmp/northwind.groovy
${LATEST_DIRECTORY}/bin/gremlin.sh -i /tmp/northwind.groovy

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VertexLabel Property Description

region

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The code or name for a specific region.

country

name

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category

name

The name of a specific category.

customer

customerId

The well-known Northwind customer identifier (e.g. ALFKI).

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老王app下载2.2.8

This sample shows how to query all categories.

SQL

SELECT *
  FROM Categories

Gremlin

gremlin> g.V().hasLabel("category").valueMap()
==>[name:[Beverages],description:[Soft drinks, coffees, teas, beers, and ales]]
==>[name:[Condiments],description:[Sweet and savory sauces, relishes, spreads, and seasonings]]
==>[name:[Confections],description:[Desserts, candies, and sweet breads]]
==>[name:[Dairy Products],description:[Cheeses]]
==>[name:[Grains/Cereals],description:[Breads, crackers, pasta, and cereal]]
==>[name:[Meat/Poultry],description:[Prepared meats]]
==>[name:[Produce],description:[Dried fruit and bean curd]]
==>[name:[Seafood],description:[Seaweed and fish]]

References:

  • 老王加速器2.2.11

  • ValueMap Step

Select single column

This sample shows how to query the names of all categories.

SQL

SELECT CategoryName
  FROM Categories

Gremlin

gremlin> g.V().hasLabel("category").values("name")
==>Beverages
==>Condiments
==>Confections
==>Dairy Products
==>Grains/Cereals
==>Meat/Poultry
==>Produce
==>Seafood

References:

  • Has Step

Select multiple columns

This sample shows how to query the names and descriptions of all categories.

SQL

SELECT CategoryName, Description
  FROM Categories

老王2.2.11下载安卓版

gremlin> g.V().hasLabel("category").valueMap("name", "description")
==>[name:[Beverages],description:[Soft drinks, coffees, teas, beers, and ales]]
==>[name:[Condiments],description:[Sweet and savory sauces, relishes, spreads, and seasonings]]
==>[name:[Confections],description:[Desserts, candies, and sweet breads]]
==>[name:[Dairy Products],description:[Cheeses]]
==>[name:[Grains/Cereals],description:[Breads, crackers, pasta, and cereal]]
==>[name:[Meat/Poultry],description:[Prepared meats]]
==>[name:[Produce],description:[Dried fruit and bean curd]]
==>[name:[Seafood],description:[Seaweed and fish]]

References:

  • Has Step

  • ValueMap Step

Select calculated column

This sample shows how to query the length of the name of all categories.

SQL

SELECT LEN(CategoryName)
  老王app下载2.2.8 Categories

Gremlin

gremlin> g.V().hasLabel("category").values("name").
               map {it.get().length()}
==>9
==>10
==>11
==>14
==>14
==>12
==>7
==>7

References:

  • Has Step

  • 老王2.2.11下载安卓版

  • String::length()

老王加速器2.2.11

This sample shows how to query all distinct lengths of category names.

SQL

SELECT DISTINCT LEN(CategoryName)
  FROM Categories

Gremlin

gremlin> g.V().hasLabel("category").values("name").
               map {it.get().length()}.dedup()
==>9
==>10
==>11
==>14
==>12
==>7

References:

  • 老王2.2.11最新版

  • Has Step

  • Lambda Steps

  • 老王加速器

老王2.2.11最新版

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SQL

老王2.2.11最新版 MAX(LEN(CategoryName))
  FROM Categories

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References:

  • Has Step

  • Lambda Steps

  • Max Step

  • String::length()

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Filter by equality

This sample shows how to query all products having no unit in stock.

SQL

SELECT ProductName, UnitsInStock
  FROM Products
 WHERE UnitsInStock = 0

Gremlin

gremlin> g.V().has("product", "unitsInStock", 0).valueMap("name", "unitsInStock")
==>[unitsInStock:[0],name:[Chef Anton's Gumbo Mix]]
==>[unitsInStock:[0],name:[Alice Mutton]]
==>[unitsInStock:[0],name:[Thüringer Rostbratwurst]]
==>[unitsInStock:[0],name:[Gorgonzola Telino]]
==>[unitsInStock:[0],name:[Perth Pasties]]

References:

  • Has Step

  • ValueMap Step

Filter by inequality

This sample shows how to query all products where the number of units on order is not 0.

SQL

SELECT ProductName, UnitsOnOrder
  FROM Products
 WHERE NOT(UnitsOnOrder = 0)

Gremlin

gremlin> g.V().has("product", "unitsOnOrder", neq(0)).
               valueMap("name", "unitsOnOrder")
==>[name:[Chang],unitsOnOrder:[40]]
==>[name:[Aniseed Syrup],unitsOnOrder:[70]]
==>[name:[Queso Cabrales],unitsOnOrder:[30]]
==>[name:[Sir Rodney's Scones],unitsOnOrder:[40]]
==>[name:[Gorgonzola Telino],unitsOnOrder:[70]]
==>[name:[Mascarpone Fabioli],unitsOnOrder:[40]]
==>[name:[Gravad lax],unitsOnOrder:[50]]
==>[name:[Ipoh Coffee],unitsOnOrder:[10]]
==>[name:[Rogede sild],unitsOnOrder:[70]]
==>[name:[Chocolade],unitsOnOrder:[70]]
...

References:

  • 老王2.2.11最新版

  • ValueMap Step

  • 老王vpm2.28下载安卓版

老王 v p v官网

This sample shows how to query all products with a minimum price of 5 and maximum price below 10.

SQL

SELECT ProductName, UnitPrice
  FROM Products
 WHERE UnitPrice >= 5 AND UnitPrice < 10

Gremlin

gremlin> g.V().has("product", "unitPrice", between(5f, 10f)).
               valueMap("name", "unitPrice")
==>[unitPrice:[6.0],name:[Konbu]]
==>[unitPrice:[9.2],name:[Teatime Chocolate Biscuits]]
==>[unitPrice:[9.0],name:[Tunnbröd]]
==>[unitPrice:[9.65],name:[Jack's New England Clam Chowder]]
==>[unitPrice:[9.5],name:[Rogede sild]]
==>[unitPrice:[9.5],name:[Zaanse koeken]]
==>[unitPrice:[7.0],name:[Filo Mix]]
==>[unitPrice:[7.45],name:[Tourtière]]
==>[unitPrice:[7.75],name:[Rhönbräu Klosterbier]]

References:

  • Has Step

  • ValueMap Step

  • A Note on Predicates

Multiple filter conditions

This sample shows how to query all discontinued products that are still not out of stock.

SQL

SELECT ProductName, UnitsInStock
  老王加速器下载官网 Products
 WHERE Discontinued = 1
   AND UnitsInStock <> 0

Gremlin

gremlin> g.V().has("product", "discontinued", true).has("unitsInStock", neq(0)).
              valueMap("name", "unitsInStock")
==>[unitsInStock:[29],name:[Mishi Kobe Niku]]
==>[unitsInStock:[20],name:[Guaraná Fantástica]]
==>[unitsInStock:[26],name:[Rössle Sauerkraut]]
==>[unitsInStock:[26],name:[Singaporean Hokkien Fried Mee]]

References:

  • Has Step

  • ValueMap Step

  • A Note on Predicates

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Order by value ascending

This sample shows how to query all products ordered by unit price.

SQL

  SELECT ProductName, UnitPrice
    FROM Products
ORDER BY UnitPrice ASC

老王2.2.11下载安卓版

gremlin> g.V().hasLabel("product").order().by("unitPrice", incr).
               valueMap("name", "unitPrice")
==>[unitPrice:[2.5],name:[Geitost]]
==>[unitPrice:[4.5],name:[Guaraná Fantástica]]
==>[unitPrice:[6.0],name:[Konbu]]
==>[unitPrice:[7.0],name:[Filo Mix]]
==>[unitPrice:[7.45],name:[Tourtière]]
==>[unitPrice:[7.75],name:[Rhönbräu Klosterbier]]
==>[unitPrice:[9.0],name:[Tunnbröd]]
==>[unitPrice:[9.2],name:[Teatime Chocolate Biscuits]]
==>[unitPrice:[9.5],name:[Rogede sild]]
==>[unitPrice:[9.5],name:[Zaanse koeken]]
...

latern专业破解版安卓最新版

  • 老王vpm2.2.11下载安卓版

  • Order Step

  • ValueMap Step

Order by value descending

This sample shows how to query all products ordered by descending unit price.

SQL

  SELECT ProductName, UnitPrice
    FROM Products
ORDER BY UnitPrice DESC

老王加速器下载官网

gremlin> g.V().hasLabel("product").order().by("unitPrice", decr).
               valueMap("name", "unitPrice")
==>[unitPrice:[263.5],name:[Côte de Blaye]]
==>[unitPrice:[123.79],name:[Thüringer Rostbratwurst]]
==>[unitPrice:[97.0],name:[Mishi Kobe Niku]]
==>[unitPrice:[81.0],name:[Sir Rodney's Marmalade]]
==>[unitPrice:[62.5],name:[Carnarvon Tigers]]
==>[unitPrice:[55.0],name:[Raclette Courdavault]]
==>[unitPrice:[53.0],name:[Manjimup Dried Apples]]
==>[unitPrice:[49.3],name:[Tarte au sucre]]
==>[unitPrice:[46.0],name:[Ipoh Coffee]]
==>[unitPrice:[45.6],name:[Rössle Sauerkraut]]
...

References:

  • Has Step

  • Order Step

  • ValueMap Step

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Limit number of results

This sample shows how to query the first 5 products ordered by unit price.

SQL

  SELECT TOP (5) ProductName, UnitPrice
    FROM Products
latern专业破解版安卓最新版 BY UnitPrice

Gremlin

gremlin> g.V().hasLabel("product").order().by("unitPrice", incr).limit(5).
               valueMap("name", "unitPrice")
==>[unitPrice:[2.5],name:[Geitost]]
==>[unitPrice:[4.5],name:[Guaraná Fantástica]]
==>[unitPrice:[6.0],name:[Konbu]]
==>[unitPrice:[7.0],name:[Filo Mix]]
==>[unitPrice:[7.45],name:[Tourtière]]

References:

  • Has Step

  • Limit Step

  • Order Step

  • 老王vpm2.28下载安卓版

Paged result set

This sample shows how to query the next 5 products (page 2) ordered by unit price.

SQL

   老王佛系免费 Products.ProductName, Products.UnitPrice
     FROM (SELECT ROW_NUMBER()
                    OVER (
                      ORDER BY UnitPrice) AS [ROW_NUMBER],
                  ProductID
             FROM Products) AS SortedProducts
       INNER JOIN Products
               ON Products.ProductID = SortedProducts.ProductID
    老王app下载2.2.8 [ROW_NUMBER] BETWEEN 6 AND 10
 ORDER BY [ROW_NUMBER]

老王加速器2.2.11

gremlin> g.V().hasLabel("product").order().by("unitPrice", incr).range(5, 10).
               valueMap("name", "unitPrice")
==>[unitPrice:[7.75],name:[Rhönbräu Klosterbier]]
==>[unitPrice:[9.0],name:[Tunnbröd]]
==>[unitPrice:[9.2],name:[Teatime Chocolate Biscuits]]
==>[unitPrice:[9.5],name:[Rogede sild]]
==>[unitPrice:[9.5],name:[Zaanse koeken]]

References:

  • Has Step

  • Range Step

  • Order Step

  • ValueMap Step

烧饼哥加速器-烧饼哥加速器官网-outline加速器密钥免费线路节点

Group by value

This sample shows how to determine the most used unit price.

SQL

  SELECT TOP(1) UnitPrice
    FROM (SELECT Products.UnitPrice,
                 COUNT(*) AS [Count]
            老王加速器下载官网 Products
        GROUP BY Products.UnitPrice) AS T
ORDER BY [Count] DESC

Gremlin

gremlin> g.V().hasLabel("product").groupCount().by("unitPrice").
               order(local).by(values, decr).select(keys).limit(local, 1)
==>18.0

References:

  • Has Step

  • GroupCount Step

  • Limit Step

  • Order Step

  • Select Step

  • 老王2.2.11下载安卓版

烧饼哥加速器-烧饼哥加速器官网-outline加速器密钥免费线路节点

旋风加速器

This sample shows how to query all products from a specific category.

SQL

    latern专业破解版安卓最新版 Products.ProductName
      FROM Products
INNER JOIN Categories
        ON Categories.CategoryID = Products.CategoryID
     WHERE Categories.CategoryName = 'Beverages'

Gremlin

gremlin> g.V().has("name","Beverages").in("inCategory").values("name")
==>Chai
==>Rhönbräu Klosterbier
==>Chartreuse verte
==>Chang
==>Lakkalikööri
==>Ipoh Coffee
==>Guaraná Fantástica
==>Côte de Blaye
==>Steeleye Stout
==>Outback Lager
...

老王2.2.11下载ios

  • Has Step

  • Vertex Steps

老王vpm2.28下载安卓版

This sample shows how to count the number of orders for each customer.

SQL

    老王加速器2.2.11 Customers.CustomerID, COUNT(Orders.OrderID)
      老王vpm2.28下载安卓版 Customers
 LEFT JOIN Orders
        ON Orders.CustomerID = Customers.CustomerID
  老王加速器下载官网 BY Customers.CustomerID

Gremlin

gremlin> g.V().hasLabel("customer").match(
           __.as("c").values("customerId").as("customerId"),
           __.as("c").out("ordered").count().as("orders")
         ).select("customerId", "orders")
==>[customerId:ALFKI,orders:6]
==>[customerId:ANATR,orders:4]
==>[customerId:ANTON,orders:7]
==>[customerId:AROUT,orders:13]
==>[customerId:BERGS,orders:18]
==>[customerId:BLAUS,orders:7]
==>[customerId:BLONP,orders:11]
==>[customerId:BOLID,orders:3]
==>[customerId:BONAP,orders:17]
==>[customerId:BOTTM,orders:14]
...

References:

  • As Step

  • Count Step

  • Has Step

  • Match Step

  • Select Step

  • Vertex Steps

烧饼哥加速器-烧饼哥加速器官网-outline加速器密钥免费线路节点

Concatenate

This sample shows how to concatenate two result sets (customers whos company name starts with A and customers whos company name starts with E).

SQL

SELECT [customer].[CompanyName]
  FROM [Customers] AS [customer]
 WHERE [customer].[CompanyName] LIKE 'A%'
 UNION ALL
SELECT [customer].[CompanyName]
  FROM [Customers] AS [customer]
 WHERE [customer].[CompanyName] LIKE 'E%'

Gremlin

gremlin> g.V().hasLabel("customer").union(
           filter {it.get().value("company")[0] == "A"},
           filter {it.get().value("company")[0] == "E"}).values("company")
==>Alfreds Futterkiste
==>Ana Trujillo Emparedados y helados
==>Antonio Moreno Taquería
==>Around the Horn
==>Eastern Connection
==>Ernst Handel

References:

  • 老王app下载2.2.8

  • Lambda Steps

  • Union Step

Create, Update and Delete

This sample shows how to create new vertices and edges, how to update them and finally how to delete them.

SQL

INSERT INTO [Categories] ([CategoryName], [Description])
     VALUES (N'Merchandising', N电一王者隔壁老王 直播_英雄联盟 直播_企鹅电竞 - QQ:2 天前 · 欢迎来到企鹅电竞电一王者隔壁老王的英雄联盟直播间,这个人很懒...。如果觉得电一王者隔壁老王直播精彩的话,别忘记关注一波。希望能给大家带来快乐。)

INSERT INTO [Products] ([ProductName], [CategoryID])
     SELECT TOP (1) N'Red Gremlin Jacket', [CategoryID]
       老王app下载2.2.8 [Categories]
      WHERE [CategoryName] = N'Merchandising'

UPDATE [Products]
   SET [Products].[ProductName] = N'Green Gremlin Jacket'
 WHERE [Products].[ProductName] = N'Red Gremlin Jacket'

DELETE FROM [Products]
 老王加速器下载官网 [Products].[ProductName] = N'Green Gremlin Jacket'

DELETE FROM [Categories]
 WHERE [Categories].[CategoryName] = N'Merchandising'

Gremlin

gremlin> c = graph.addVertex(label, "category",
                   "name", "Merchandising",
                   "description", "Cool products to promote Gremlin")
==>v[0]
gremlin>
gremlin> p = graph.addVertex(label, "product",
                   "name", "Red Gremlin Jacket")
==>v[3]
gremlin>
gremlin> p.addEdge("inCategory", c)
==>e[5][3-inCategory->0]
gremlin>
gremlin> g.V().has("product", "name", "Red Gremlin Jacket").
               property("name", "Green Gremlin Jacket").iterate()
gremlin>
gremlin> p.remove()
==>null
gremlin> g.V().has("category", "name", "Merchandising").drop()

老王永久佛系

  • Mutating the Graph

  • Has Step

  • Drop Step

CTE

Recursive query

This sample shows how to query all employees, their supervisors and their hierarchy level depending on where the employee is located in the supervisor chain.

SQL

WITH EmployeeHierarchy (EmployeeID,
                        LastName,
                        FirstName,
                        ReportsTo,
                        HierarchyLevel) AS
(
    SELECT EmployeeID
         , LastName
         , FirstName
         , ReportsTo
         , 1 as HierarchyLevel
      FROM Employees
     WHERE ReportsTo IS NULL

     UNION ALL

    SELECT e.EmployeeID
         , e.LastName
         , e.FirstName
         , e.ReportsTo
         , eh.HierarchyLevel + 1 AS HierarchyLevel
      FROM Employees e
INNER JOIN EmployeeHierarchy eh
        ON e.ReportsTo = eh.EmployeeID
)
  老王v p n *
    FROM EmployeeHierarchy
ORDER BY HierarchyLevel, LastName, FirstName

Gremlin (hierarchical)

gremlin> g.V().hasLabel("employee").where(__.not(out("reportsTo"))).
               repeat(__.in("reportsTo")).emit().tree().by(map {
                 def employee = it.get()
                 employee.value("firstName") + " " + employee.value("lastName")
               }).next()
==>Andrew Fuller={Margaret Peacock={}, Janet Leverling={}, Nancy Davolio={}, Steven Buchanan={Anne Dodsworth={}, Michael Suyama={}, Robert King={}}, Laura Callahan={}}

You can also produce the same tabular result that’s produced by SQL.

Gremlin (tabular)

gremlin> g.V().hasLabel("employee").where(__.not(out("reportsTo"))).
               repeat(__.as("reportsTo").in("reportsTo").as("employee")).emit().
               select(last, "reportsTo", "employee").by(map {
                 def employee = it.get()
                 employee.value("firstName") + " " + employee.value("lastName")
               })
==>[reportsTo:Andrew Fuller,employee:Nancy Davolio]
==>[reportsTo:Andrew Fuller,employee:Janet Leverling]
==>[reportsTo:Andrew Fuller,employee:Margaret Peacock]
==>[reportsTo:Andrew Fuller,employee:Steven Buchanan]
==>[reportsTo:Andrew Fuller,employee:Laura Callahan]
==>[reportsTo:Steven Buchanan,employee:Robert King]
==>[reportsTo:Steven Buchanan,employee:Anne Dodsworth]
==>[reportsTo:Steven Buchanan,employee:Michael Suyama]

References:

  • As Step

  • Has Step

  • 老王加速器下载官网

  • Repeat Step

  • Select Step

  • Vertex Steps

  • Tree Step

  • Where Step

Complex

Pivots

This sample shows how to determine the average total order value per month for each customer.

SQL

    SELECT Customers.CompanyName,
           COALESCE([1], 0)  AS [Jan],
           COALESCE([2], 0)  AS [Feb],
           COALESCE([3], 0)  AS [Mar],
           COALESCE([4], 0)  AS [Apr],
           COALESCE([5], 0)  AS [May],
           COALESCE([6], 0)  AS [Jun],
           COALESCE([7], 0)  AS [Jul],
           COALESCE([8], 0)  AS [Aug],
           COALESCE([9], 0)  AS [Sep],
           COALESCE([10], 0) AS [Oct],
           COALESCE([11], 0) AS [Nov],
           COALESCE([12], 0) AS [Dec]
      FROM (SELECT Orders.CustomerID,
                   MONTH(Orders.OrderDate)                                   AS [Month],
                   SUM([Order Details].UnitPrice * [Order Details].Quantity) AS Total
              FROM Orders
        INNER 老王2.2.11最新版 [Order Details]
                ON [Order Details].OrderID = Orders.OrderID
          GROUP BY Orders.CustomerID,
                   MONTH(Orders.OrderDate)) o
     PIVOT (AVG(Total) FOR [Month] IN ([1],
                                       [2],
                                       [3],
                                       [4],
                                       [5],
                                       [6],
                                       [7],
                                       [8],
                                       [9],
                                       [10],
                                       [11],
                                       [12])) AS [Pivot]
INNER JOIN Customers
        ON Customers.CustomerID = [Pivot].CustomerID
  老王加速器下载官网 BY Customers.CompanyName

Gremlin

gremlin> months = new java.text.DateFormatSymbols().getShortMonths().toList(); []
gremlin> rowTotal = {it.get().value("unitPrice") * it.get().value("quantity")}; []
gremlin>
gremlin> g.V().hasLabel("customer").order().by("customerId", incr).
               where(out("ordered")).as("customer").
               map {
                 def m = g.V(it.get()).out("ordered").
                           group().by {new Date(it.value("orderDate")).getMonth()}.
                                   by(out("contains").map(rowTotal).sum()).next()
                 (0..11).collectEntries {[months[it], m.containsKey(it) ? m[it] : 0]}
               }.as("totals").select("customer", "totals").by(id).by()
==>[customer:8,totals:[Jan:851.0,Feb:0,Mar:491.2,Apr:960.00,May:0,Jun:0,Jul:0,Aug:1086.0,Sep:0,Oct:1208.0,Nov:0,Dec:0]]
==>[customer:9,totals:[Jan:0,Feb:0,Mar:514.4,Apr:0,May:0,Jun:0,Jul:0,Aug:479.75,Sep:88.8,Oct:0,Nov:320.0,Dec:0]]
==>[customer:10,totals:[Jan:660.0,Feb:0,Mar:0,Apr:881.25,May:2156.5,Jun:2082.0,Jul:0,Aug:0,Sep:1332.40,Oct:0,Nov:403.2,Dec:0]]
==>[customer:11,totals:[Jan:0,Feb:735.0,Mar:5065.00,Apr:491.5,May:0,Jun:2142.9,Jul:0,Aug:0,Sep:0,Oct:1704.0,Nov:1101.0,Dec:2567.10]]
==>[customer:12,totals:[Jan:3884.95,Feb:3397.70,Mar:2034.50,Apr:3192.65,May:0,Jun:1565.65,Jul:0,Aug:3605.6,Sep:5509.20,Oct:0,Nov:1459.00,Dec:2318.90]]
==>[customer:13,totals:[Jan:625.0,Feb:0,Mar:677.0,Apr:1143.80,May:0,Jun:330.0,Jul:464.0,Aug:0,Sep:0,Oct:0,Nov:0,Dec:0]]
==>[customer:14,totals:[Jan:730.0,Feb:4049.0,Mar:0,Apr:0,May:0,Jun:3212.80,Jul:1176.0,Aug:450.0,Sep:2080.0,Oct:0,Nov:7390.2,Dec:0]]
==>[customer:15,totals:[Jan:0,Feb:0,Mar:280.0,Apr:0,May:0,Jun:0,Jul:0,Aug:0,Sep:0,Oct:982.0,Nov:0,Dec:4035.80]]
==>[customer:16,totals:[Jan:843.0,Feb:3000.40,Mar:4106.30,Apr:3000.0,May:1903.00,Jun:0,Jul:0,Aug:0,Sep:2032.0,Oct:3948.9,Nov:5017.35,Dec:0]]
==>[customer:17,totals:[Jan:4533.5,Feb:0,Mar:10118.60,Apr:3004.8,May:0,Jun:0,Jul:0,Aug:0,Sep:0,Oct:0,Nov:3118.0,Dec:1832.8]]
...

References:

  • 老王2.2.11下载ios

  • 老王2.2.11最新版

  • Has Step

  • Order Step

  • Select Step

  • Sum Step

  • Where Step

  • Vertex Steps

  • Transform Collection to a Map with collectEntries

  • DateFormatSymbols::getShortMonths()

老王2.2.11下载安卓版

This sample shows how to recommend 5 products for a specific customer. The products are chosen as follows:

  • determine what the customer has already ordered

  • determine who else ordered the same products

  • determine what others also ordered

  • determine products which were not already ordered by the initial customer, but ordered by the others

  • rank products by occurence in other orders

SQL

  SELECT TOP (5) [t14].[ProductName]
    FROM (SELECT COUNT(*) AS [value],
                 [t13].[ProductName]
            FROM [customers] AS [t0]
     老王下载地址官网 APPLY (SELECT [t9].[ProductName]
                    FROM [orders] AS [t1]
              CROSS JOIN [order details] AS [t2]
              INNER JOIN [products] AS [t3]
                      ON [t3].[ProductID] = [t2].[ProductID]
              CROSS JOIN [order details] AS [t4]
              INNER JOIN [orders] AS [t5]
                      ON [t5].[OrderID] = [t4].[OrderID]
               LEFT JOIN [customers] AS [t6]
                      ON [t6].[CustomerID] = [t5].[CustomerID]
              CROSS JOIN ([orders] AS [t7]
                          CROSS JOIN [order details] AS [t8]
                          INNER JOIN [products] AS [t9]
                                  ON [t9].[ProductID] = [t8].[ProductID])
                   WHERE NOT 老王2.2.11下载ios(SELECT NULL AS [EMPTY]
                                      FROM [orders] AS [t10]
                                CROSS JOIN [order details] AS [t11]
                                INNER 老王永久佛系 [products] AS [t12]
                                        ON [t12].[ProductID] = [t11].[ProductID]
                                     WHERE [t9].[ProductID] = [t12].[ProductID]
                                       AND [t10].[CustomerID] = [t0].[CustomerID]
                                       AND [t11].[OrderID] = [t10].[OrderID])
                     AND [t6].[CustomerID] <> [t0].[CustomerID]
                     AND [t1].[CustomerID] = [t0].[CustomerID]
                     AND [t2].[OrderID] = [t1].[OrderID]
                     AND [t4].[ProductID] = [t3].[ProductID]
                     AND [t7].[CustomerID] = [t6].[CustomerID]
                     AND [t8].[OrderID] = [t7].[OrderID]) AS [t13]
           老王2.2.11最新版 [t0].[CustomerID] = N'ALFKI'
        GROUP BY [t13].[ProductName]) AS [t14]
latern专业破解版安卓最新版 BY [t14].[value] 老王加速器下载官网

Gremlin

gremlin> g.V().has("customer", "customerId", "ALFKI").as("customer").
               out("ordered").out("contains").out("is").aggregate("products").
               in("is").in("contains").in("ordered").where(neq("customer")).
               out("ordered").out("contains").out("is").where(without("products")).
               groupCount().order(local).by(values, decr).select(keys).limit(local, 5).
               unfold().values("name")
==>Gorgonzola Telino
==>Guaraná Fantástica
==>Camembert Pierrot
==>Chang
==>Jack's New England Clam Chowder

References:

  • 老王2.2.11最新版

  • As Step

  • GroupCount Step

  • Has Step

  • Limit Step

  • Order Step

  • Select Step

  • Unfold Step

  • Vertex Steps

  • 老王加速器2.2.11

  • A Note on Predicates


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