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--- project-3-draft [2021/04/22 11:06]
roxana_elena.stiuca [Graph queries]
+++ project-3-draft [2021/04/25 16:07] (current)
roxana_elena.stiuca prerequisite for taskset3
@@ Line 26: / Line 26: @@
     | Cartesian (Row -> Row -> Row) [String] Query Query
     | Projection [String] Query
---    | forall a. Filter (FilterCondition a) Query
+    | forall a. FEval a => Filter (FilterCondition a) Query
-    | Graph EdgeOp query
+    | Graph EdgeOp Query
 -- where EdgeOp is defined:
@@ Line 34: / Line 34: @@
 **Don't worry about Graph or Filter queries yet.**
+==== Prerequisite ====
+Add the following lines at the beginning of your .hs files:
+<code haskell>
+{-# LANGUAGE ExistentialQuantification #-}
+{-# LANGUAGE FlexibleInstances #-}
+</code>
+The first line allows ''forall a''.
+The second allows ''instance FEval String''.
 ===== Query Evaluation =====
@@ Line 128: / Line 137: @@
 A **graph** is a special kind of table which has precisely the following column names: ''["From", "To", "Value"]''. Each row defines a **weighted edge** between node ''From'' and node ''To''.
-The query ''Graph edgeop query'': creates a graph starting from the result of the evaluation of ''query''. Say **T** is that table.
+The query ''Graph edgeop query'': creates such a table starting from the result of the evaluation of ''query''. Suppose the query evaluates to a table **T**.
-  * The nodes are the rows in table **T**.
+  * The nodes are the **rows** in table **T**.
-  * The weight of an edge between 2 nodes is given by ''edgeop'', which returns a Maybe Value. If ''edgeop row1 row2'' returns ''Nothing'', then we don't have an edge between those 2 nodes. If it returns ''Just val'' then we have an edge between row1 and row2 of weight val.
+  * The weight of an edge between 2 nodes is given by ''edgeop'', which returns a ''Maybe Value''. If ''edgeop row1 row2'' returns ''Nothing'', then we don't have an edge between those 2 nodes. If it returns ''Just val'' then we have an edge between ''row1'' and ''row2'' of weight ''val''.
-  * In the resulting table, a row describes an edge between node_i and node_j and will have the values:
+  * In the resulting table, each row describes an edge between node_i and node_j and will have the values:
     * "From" = first column from node_i
     * "To" = first column from node_j
     * "Value" = edgeop node_i node_j
-The edge node_i-node_j is the same as node_j-node_i, so it should only appear once. "From" value should be lexicographically before "To".
+The edge //node_i-node_j// is the same as //node_j-node_i//, so it should only appear once (graphs are unoriented). "From" value should be lexicographically before "To".
+**Example:** Suppose **T** is the table shown below:
+<code>
+Name      Grade      Class
+Mihai     9          321
+Andrei    8          322
+Stefan    10         321
+Ana       9          322
+</code>
+If we would like to build a graph that connects all students in the same class, then:
+<code haskell>
+edgeop [_,_,z] [_,_,c]
+   | z == c = Just c
+   | otherwise = Nothing
+</code>
+and the resulting graph will be:
+<code>
+From      To      Value
+Mihai     Stefan  321
+Ana       Andrei  322
+</code>
+If we would like to build a graph that connects students with grades equal or with a difference of **at least** a point, then:
+<code haskell>
+edgeop [_,x,_] [_,y,_]
+   | abs $ (read x :: Int) - (read y :: Int) <= 1 = Just "similar"
+   | otherwise = Nothing
+</code>
+and the resulting graph is:
+<code>
+From      To      Value
+Andrei    Mihai   similar
+Mihai     Stefan  similar
+Ana       Mihai   similar
+Ana       Andrei  similar
+Ana       Stefan  similar
+</code>
 ==== Similarities graph, using queries ====
 We want to check the similarities between students lecture points.
   * For that, we want to obtain a graph where "From" and "To" are students' emails and "Value" is the distance between the 2 students' points.
@@ Line 145: / Line 196: @@
   * The edges in the resulting graph (the rows in the resulting table) should be sorted by the "Value" column. If email is missing, don't include that entry.
-Your task is to write ''similarities_query'' as a sequence of queries, that once evaluated results in the graph described above.
+Your task is to write ''similarities_query'' as a **sequence of queries**, that once evaluated results in the graph described above.
+**Note**: ''similarities_query'' is a Query. The checker applies ''eval'' on it.
 ===== TL;DR Tasks =====
-  - Enroll Query in class Eval (without Filter or Graph). 0.3p
+  - Enroll ''Query'' in class ''Eval'' (without ''Filter'' or ''Graph''). **0.3p**
-  -  Enroll FilterCondition in class FEval and implement eval for Filter query. 0.2p
+  - Enroll ''FilterCondition'' in class ''FEval'' and implement ''eval'' for ''Filter'' query. **0.2p**
-  - Implement eval for Graph query. 0.2p
+  - Implement ''eval'' for ''Graph'' query. 0.2p
-  - Get graph for similarities. 0.3p
+  - Extract similarity graph. 0.3p
 ===== Checker =====