Summary: * Prefix filenames with order in which they should appear in the sidebar. * Fix links Reviewers: buda Reviewed By: buda Differential Revision: https://phabricator.memgraph.io/D1618
8.5 KiB
Reading Existing Data
The simplest usage of the language is to find data stored in the database. For that purpose, the following clauses are offered:
MATCH
, which searches for patterns;WHERE
, for filtering the matched data andRETURN
, for defining what will be presented to the user in the result set.UNION
andUNION ALL
for combining results from multiple queries.
MATCH
This clause is used to obtain data from Memgraph by matching it to a given pattern. For example, to find each node in the database, you can use the following query.
MATCH (node) RETURN node
Finding connected nodes can be achieved by using the query:
MATCH (node1)-[connection]-(node2) RETURN node1, connection, node2
In addition to general pattern matching, you can narrow the search down by
specifying node labels and properties. Similarly, edge types and properties
can also be specified. For example, finding each node labeled as Person
and
with property age
being 42, is done with the following query.
MATCH (n :Person {age: 42}) RETURN n
While their friends can be found with the following.
MATCH (n :Person {age: 42})-[:FriendOf]-(friend) RETURN friend
There are cases when a user needs to find data which is connected by
traversing a path of connections, but the user doesn't know how many
connections need to be traversed. openCypher allows for designating patterns
with variable path lengths. Matching such a path is achieved by using the
*
(asterisk) symbol inside the edge element of a pattern. For example,
traversing from node1
to node2
by following any number of connections in a
single direction can be achieved with:
MATCH (node1)-[r*]->(node2) RETURN node1, r, node2
If paths are very long, finding them could take a long time. To prevent that, a user can provide the minimum and maximum length of the path. For example, paths of length between 2 and 4 can be obtained with a query like:
MATCH (node1)-[r*2..4]->(node2) RETURN node1, r, node2
It is possible to name patterns in the query and return the resulting paths. This is especially useful when matching variable length paths:
MATCH path = ()-[r*2..4]->() RETURN path
More details on how MATCH
works can be found
here.
The MATCH
clause can be modified by prepending the OPTIONAL
keyword.
OPTIONAL MATCH
clause behaves the same as a regular MATCH
, but when it
fails to find the pattern, missing parts of the pattern will be filled with
null
values. Examples can be found
here.
WHERE
You have already seen that simple filtering can be achieved by using labels
and properties in MATCH
patterns. When more complex filtering is desired,
you can use WHERE
paired with MATCH
or OPTIONAL MATCH
. For example,
finding each person older than 20 is done with the this query.
MATCH (n :Person) WHERE n.age > 20 RETURN n
Additional examples can be found here.
RETURN
The RETURN
clause defines which data should be included in the resulting
set. Basic usage was already shown in the examples for MATCH
and WHERE
clauses. Another feature of RETURN
is renaming the results using the AS
keyword.
Example.
MATCH (n :Person) RETURN n AS people
That query would display all nodes under the header named people
instead of
n
.
When you want to get everything that was matched, you can use the *
(asterisk) symbol.
This query:
MATCH (node1)-[connection]-(node2) RETURN *
is equivalent to:
MATCH (node1)-[connection]-(node2) RETURN node1, connection, node2
RETURN
can be followed by the DISTINCT
operator, which will remove
duplicate results. For example, getting unique names of people can be achieved
with:
MATCH (n :Person) RETURN DISTINCT n.name
Besides choosing what will be the result and how it will be named, the
RETURN
clause can also be used to:
- limit results with
LIMIT
sub-clause; - skip results with
SKIP
sub-clause; - order results with
ORDER BY
sub-clause and - perform aggregations (such as
count
).
More details on RETURN
can be found
here.
SKIP & LIMIT
These sub-clauses take a number of how many results to skip or limit. For example, to get the first 3 results you can use this query.
MATCH (n :Person) RETURN n LIMIT 3
If you want to get all the results after the first 3, you can use the following.
MATCH (n :Person) RETURN n SKIP 3
The SKIP
and LIMIT
can be combined. So for example, to get the 2nd result,
you can do:
MATCH (n :Person) RETURN n SKIP 1 LIMIT 1
ORDER BY
Since the patterns which are matched can come in any order, it is very useful
to be able to enforce some ordering among the results. In such cases, you can
use the ORDER BY
sub-clause.
For example, the following query will get all :Person
nodes and order them
by their names.
MATCH (n :Person) RETURN n ORDER BY n.name
By default, ordering will be in the ascending order. To change the order to be
descending, you should append DESC
.
For example, to order people by their name descending, you can use this query.
MATCH (n :Person) RETURN n ORDER BY n.name DESC
You can also order by multiple variables. The results will be sorted by the first variable listed. If the values are equal, the results are sorted by the second variable, and so on.
Example. Ordering by first name descending and last name ascending.
MATCH (n :Person) RETURN n ORDER BY n.name DESC, n.lastName
Note that ORDER BY
sees only the variable names as carried over by RETURN
.
This means that the following will result in an error.
MATCH (n :Person) RETURN old AS new ORDER BY old.name
Instead, the new
variable must be used:
MATCH (n: Person) RETURN old AS new ORDER BY new.name
The ORDER BY
sub-clause may come in handy with SKIP
and/or LIMIT
sub-clauses. For example, to get the oldest person you can use the following.
MATCH (n :Person) RETURN n ORDER BY n.age DESC LIMIT 1
Aggregating
openCypher has functions for aggregating data. Memgraph currently supports the following aggregating functions.
avg
, for calculating the average.collect
, for collecting multiple values into a single list or map. If given a single expression values are collected into a list. If given two expressions, values are collected into a map where the first expression denotes map keys (must be string values) and the second expression denotes map values.count
, for counting the resulting values.max
, for calculating the maximum result.min
, for calculating the minimum result.sum
, for getting the sum of numeric results.
Example, calculating the average age:
MATCH (n :Person) RETURN avg(n.age) AS averageAge
Collecting items into a list:
MATCH (n :Person) RETURN collect(n.name) AS list_of_names
Collecting items into a map:
MATCH (n :Person) RETURN collect(n.name, n.age) AS map_name_to_age
Click here for additional details on how aggregations work.
UNION and UNION ALL
openCypher supports combining results from multiple queries into a single result set. That result will contain rows that belong to queries in the union respecting the union type.
Using UNION
will contain only distinct rows while UNION ALL
will keep all
rows from all given queries.
Restrictions when using UNION
or UNION ALL
:
- The number and the names of columns returned by queries must be the same for all of them.
- There can be only one union type between single queries, i.e. a query can't
contain both
UNION
andUNION ALL
.
Example, get distinct names that are shared between persons and movies:
MATCH(n: Person) RETURN n.name AS name UNION MATCH(n: Movie) RETURN n.name AS name
Example, get all names that are shared between persons and movies (including duplicates):
MATCH(n: Person) RETURN n.name AS name UNION ALL MATCH(n: Movie) RETURN n.name AS name