Related
id | name | ipAddress
----+----------+-------------------------
1 | testname | {192.168.1.60,192.168.1.65}
I want to search ipAddress with LIKE. I tried:
{'$mac_ip_addresses.ip_address$': { [OP.contains]: [searchItem]}},
This one also:
{'$mac_ip_addresses.ip_address$': { [OP.Like] : { [OP.any]: [searchItem]}}},
The data type of ipAddress is text[]. I want to search in ipAddress with LIKE.
searchItem contains the IP that need to be searched in the ipAddress field so I want to search in array with LIKE.
I don't know Sequelize but I can answer from postgres side.
There is no short syntax to search for a pattern inside array in PostgreSQL.
If you want to check pattern for each array element individually, then you need to unfold the array using unnest:
SELECT id, name, ipaddress
FROM testing
WHERE EXISTS (
SELECT 1 FROM unnest(ipaddress) AS ip
WHERE ip LIKE '8.8.8.%'
);
If the array is frequently searched this way, it's better to store the data in normalized form.
However, there is a short syntax (plus GIN index support) for for equality based search (see #> and other operators here).
SELECT id, name, ipaddress
FROM testing
WHERE ipaddress #> ARRAY['8.8.8.8'];
What you asked
~~ is the operator used internally to implementing SQL LIKE. There is no commutator for it - no operator that works with left and right operand switched.
That's the one you'd need for your attempt to use the ANY construct with the pattern to the left. Related:
You can create the operator, though, and it's pretty simple:
CREATE OR REPLACE FUNCTION reverse_like (text, text)
RETURNS boolean LANGUAGE sql IMMUTABLE PARALLEL SAFE AS
'SELECT $2 LIKE $1';
CREATE OPERATOR <~~ (function = reverse_like, leftarg = text, rightarg = text);
Inspired by Jeff Janes' idea here:
Match string pattern to any array element
Then your query can have the pattern to the left of the operator:
SELECT *
FROM mac_ip_addresses
WHERE '192.168.2%.255' <~~ ANY (ipaddress);
Simple, but considerably slower than the EXISTS expression demonstrated by filiprem.
Then again, either query is excruciatingly slow for big tables, since neither can use an index. A normalized DB design with a n:1 table holding one IP each would allow that. It would also occupy several times the space on disk. Still, the much cleaner implementation ...
While stuck with your current design, there is still a way: create a trigram GIN index on a text representation of the array and add a redundant, "sargable" predicate to the query additionally. Confused? Here's the recipe:
First, trigram indexes? Read this if you are not familiar:
PostgreSQL LIKE query performance variations
Neither the cast from text[] to text nor array_to_string() are immutable. But we need that for an expression index. Long story short, fake it with an immutable wrapper function:
CREATE OR REPLACE FUNCTION f_textarr2text(text[])
RETURNS text LANGUAGE sql IMMUTABLE AS $$SELECT array_to_string($1, ',')$$;
CREATE INDEX iparr_trigram_idx ON iparr
USING gin (f_textarr2text(iparr) gin_trgm_ops);
Related answer with the long story (and why it's safe):
Indexing an array for full text search
Then your query can be:
SELECT *
FROM mac_ip_addresses
WHERE NOT ('192.168.9%.255' <~~ ANY (ipaddress))
AND f_textarr2text(ipaddress) LIKE '192.168.9%.255'; -- logically redundant
The added predicate is logically redundant, but can tap into the power of the trigram index.
Much faster for big tables. Still a bit faster, yet:
SELECT *
FROM mac_ip_addresses
WHERE EXISTS (SELECT FROM unnest(ipaddress) ip WHERE ip LIKE '192.168.9%.255')
AND f_textarr2text(ipaddress) LIKE '192.168.9%.255';
But that's minor now.
db<>fiddle here
I addressed the question asked, as I took an interest. Might be of interest to the general public. Most probably not what you need, though.
What you need
I want to search in ipAddress with LIKE. searchItem contains the IP that need to be searched in the ipAddress field so I want to search in array with LIKE.
That should probably read:
"I want to search a given IP address (searchItem) in the array ipAddress. My first idea is to use LIKE ..."
Well, LIKE is for pattern matching. To find complete IP addresses in an array, it's the wrong tool. filiprem's second query with array operators is the way to go. Probably good enough.
Using the built-in data type cidr instead of text would be better. And the ip4 data type of the additional ip4r module would be much better, yet. All in combination with standard array operators like demonstrated.
Finally, converting IPv4 addresses to integer and using that with the additional inrarray module should be stellar - as far as performance is concerned.
Select all records, ID which is not in the list
How to make like :
query = Story.all()
query.filter('ID **NOT IN** =', [100,200,..,..])
There's no way to do this efficiently in App Engine. You should simply select everything without that filter, and filter out any matching entities in your code.
This is now supported via GQL query
The 'IN' and '!=' operators in the Python runtime are actually
implemented in the SDK and translate to multiple queries 'under the
hood'.
For example, the query "SELECT * FROM People WHERE name IN ('Bob',
'Jane')" gets translated into two queries, equivalent to running
"SELECT * FROM People WHERE name = 'Bob'" and "SELECT * FROM People
WHERE name = 'Jane'" and merging the results. Combining multiple
disjunctions multiplies the number of queries needed, so the query
"SELECT * FROM People WHERE name IN ('Bob', 'Jane') AND age != 25"
generates a total of four queries, for each of the possible conditions
(age less than or greater than 25, and name is 'Bob' or 'Jane'), then
merges them together into a single result set.
source: appengine blog
This is an old question, so I'm not sure if the ID is a non-key property. But in order to answer this:
query = Story.all()
query.filter('ID **NOT IN** =', [100,200,..,..])
...With ndb models, you can definitely query for items that are in a list. For example, see the docs here for IN and !=. Here's how to filter as the OP requested:
query = Story.filter(Story.id.IN([100,200,..,..])
We can even query for items that in a list of repeated keys:
def all(user_id):
# See if my user_id is associated with any Group.
groups_belonged_to = Group.query().filter(user_id == Group.members)
print [group.to_dict() for group in belong_to]
Some caveats:
There's docs out there that mention that in order to perform these types of queries, Datastore performs multiple queries behind the scenes, which (1) might take a while to execute, (2) take longer if you searching in repeated properties, and (3) will up your costs with more operations.
Simple one really. In SQL, if I want to search a text field for a couple of characters, I can do:
SELECT blah FROM blah WHERE blah LIKE '%text%'
The documentation for App Engine makes no mention of how to achieve this, but surely it's a common enough problem?
BigTable, which is the database back end for App Engine, will scale to millions of records. Due to this, App Engine will not allow you to do any query that will result in a table scan, as performance would be dreadful for a well populated table.
In other words, every query must use an index. This is why you can only do =, > and < queries. (In fact you can also do != but the API does this using a a combination of > and < queries.) This is also why the development environment monitors all the queries you do and automatically adds any missing indexes to your index.yaml file.
There is no way to index for a LIKE query so it's simply not available.
Have a watch of this Google IO session for a much better and more detailed explanation of this.
i'm facing the same problem, but i found something on google app engine pages:
Tip: Query filters do not have an explicit way to match just part of a string value, but you can fake a prefix match using inequality filters:
db.GqlQuery("SELECT * FROM MyModel WHERE prop >= :1 AND prop < :2",
"abc",
u"abc" + u"\ufffd")
This matches every MyModel entity with a string property prop that begins with the characters abc. The unicode string u"\ufffd" represents the largest possible Unicode character. When the property values are sorted in an index, the values that fall in this range are all of the values that begin with the given prefix.
http://code.google.com/appengine/docs/python/datastore/queriesandindexes.html
maybe this could do the trick ;)
Altough App Engine does not support LIKE queries, have a look at the properties ListProperty and StringListProperty. When an equality test is done on these properties, the test will actually be applied on all list members, e.g., list_property = value tests if the value appears anywhere in the list.
Sometimes this feature might be used as a workaround to the lack of LIKE queries. For instance, it makes it possible to do simple text search, as described on this post.
You need to use search service to perform full text search queries similar to SQL LIKE.
Gaelyk provides domain specific language to perform more user friendly search queries. For example following snippet will find first ten books sorted from the latest ones with title containing fern
and the genre exactly matching thriller:
def documents = search.search {
select all from books
sort desc by published, SearchApiLimits.MINIMUM_DATE_VALUE
where title =~ 'fern'
and genre = 'thriller'
limit 10
}
Like is written as Groovy's match operator =~.
It supports functions such as distance(geopoint(lat, lon), location) as well.
App engine launched a general-purpose full text search service in version 1.7.0 that supports the datastore.
Details in the announcement.
More information on how to use this: https://cloud.google.com/appengine/training/fts_intro/lesson2
Have a look at Objectify here , it is like a Datastore access API. There is a FAQ with this question specifically, here is the answer
How do I do a like query (LIKE "foo%")
You can do something like a startWith, or endWith if you reverse the order when stored and searched. You do a range query with the starting value you want, and a value just above the one you want.
String start = "foo";
... = ofy.query(MyEntity.class).filter("field >=", start).filter("field <", start + "\uFFFD");
Just follow here:
init.py#354">http://code.google.com/p/googleappengine/source/browse/trunk/python/google/appengine/ext/search/init.py#354
It works!
class Article(search.SearchableModel):
text = db.TextProperty()
...
article = Article(text=...)
article.save()
To search the full text index, use the SearchableModel.all() method to get an
instance of SearchableModel.Query, which subclasses db.Query. Use its search()
method to provide a search query, in addition to any other filters or sort
orders, e.g.:
query = article.all().search('a search query').filter(...).order(...)
I tested this with GAE Datastore low-level Java API. Me and works perfectly
Query q = new Query(Directorio.class.getSimpleName());
Filter filterNombreGreater = new FilterPredicate("nombre", FilterOperator.GREATER_THAN_OR_EQUAL, query);
Filter filterNombreLess = new FilterPredicate("nombre", FilterOperator.LESS_THAN, query+"\uFFFD");
Filter filterNombre = CompositeFilterOperator.and(filterNombreGreater, filterNombreLess);
q.setFilter(filter);
In general, even though this is an old post, a way to produce a 'LIKE' or 'ILIKE' is to gather all results from a '>=' query, then loop results in python (or Java) for elements containing what you're looking for.
Let's say you want to filter users given a q='luigi'
users = []
qry = self.user_model.query(ndb.OR(self.user_model.name >= q.lower(),self.user_model.email >= q.lower(),self.user_model.username >= q.lower()))
for _qry in qry:
if q.lower() in _qry.name.lower() or q.lower() in _qry.email.lower() or q.lower() in _qry.username.lower():
users.append(_qry)
It is not possible to do a LIKE search on datastore app engine, how ever creating an Arraylist would do the trick if you need to search a word in a string.
#Index
public ArrayList<String> searchName;
and then to search in the index using objectify.
List<Profiles> list1 = ofy().load().type(Profiles.class).filter("searchName =",search).list();
and this will give you a list with all the items that contain the world you did on the search
If the LIKE '%text%' always compares to a word or a few (think permutations) and your data changes slowly (slowly means that it's not prohibitively expensive - both price-wise and performance-wise - to create and updates indexes) then Relation Index Entity (RIE) may be the answer.
Yes, you will have to build additional datastore entity and populate it appropriately. Yes, there are some constraints that you will have to play around (one is 5000 limit on the length of list property in GAE datastore). But the resulting searches are lightning fast.
For details see my RIE with Java and Ojbectify and RIE with Python posts.
"Like" is often uses as a poor-man's substitute for text search. For text search, it is possible to use Whoosh-AppEngine.
I have two tables.
In one table there are two columns, one has the ID and the other the abstracts of a document about 300-500 words long. There are about 500 rows.
The other table has only one column and >18000 rows. Each cell of that column contains a distinct acronym such as NGF, EPO, TPO etc.
I am interested in a script that will scan each abstract of the table 1 and identify one or more of the acronyms present in it, which are also present in table 2.
Finally the program will create a separate table where the first column contains the content of the first column of the table 1 (i.e. ID) and the acronyms found in the document associated with that ID.
Can some one with expertise in Python, Perl or any other scripting language help?
It seems to me that you are trying to join the two tables where the acronym appears in the abstract. ie (pseudo SQL):
SELECT acronym.id, document.id
FROM acronym, document
WHERE acronym.value IN explode(documents.abstract)
Given the desired semantics you can use the most straight forward approach:
acronyms = ['ABC', ...]
documents = [(0, "Document zeros discusses the value of ABC in the context of..."), ...]
joins = []
for id, abstract in documents:
for word in abstract.split():
try:
index = acronyms.index(word)
joins.append((id, index))
except ValueError:
pass # word not an acronym
This is a straightforward implementation; however, it has n cubed running time as acronyms.index performs a linear search (of our largest array, no less). We can improve the algorithm by first building a hash index of the acronyms:
acronyms = ['ABC', ...]
documents = [(0, "Document zeros discusses the value of ABC in the context of..."), ...]
index = dict((acronym, idx) for idx, acronym in enumberate(acronyms))
joins = []
for id, abstract in documents:
for word in abstract.split():
try
joins.append((id, index[word]))
except KeyError:
pass # word not an acronym
Of course, you might want to consider using an actual database. That way you won't have to implement your joins by hand.
Thanks a lot for the quick response.
I assume the pseudo SQL solution is for MYSQL etc. However it did not work in Microsoft ACCESS.
the second and the third are for Python I assume. Can I feed acronym and document as input files?
babru
It didn't work in Access because tables are accessed differently (e.g. acronym.[id])
Simple one really. In SQL, if I want to search a text field for a couple of characters, I can do:
SELECT blah FROM blah WHERE blah LIKE '%text%'
The documentation for App Engine makes no mention of how to achieve this, but surely it's a common enough problem?
BigTable, which is the database back end for App Engine, will scale to millions of records. Due to this, App Engine will not allow you to do any query that will result in a table scan, as performance would be dreadful for a well populated table.
In other words, every query must use an index. This is why you can only do =, > and < queries. (In fact you can also do != but the API does this using a a combination of > and < queries.) This is also why the development environment monitors all the queries you do and automatically adds any missing indexes to your index.yaml file.
There is no way to index for a LIKE query so it's simply not available.
Have a watch of this Google IO session for a much better and more detailed explanation of this.
i'm facing the same problem, but i found something on google app engine pages:
Tip: Query filters do not have an explicit way to match just part of a string value, but you can fake a prefix match using inequality filters:
db.GqlQuery("SELECT * FROM MyModel WHERE prop >= :1 AND prop < :2",
"abc",
u"abc" + u"\ufffd")
This matches every MyModel entity with a string property prop that begins with the characters abc. The unicode string u"\ufffd" represents the largest possible Unicode character. When the property values are sorted in an index, the values that fall in this range are all of the values that begin with the given prefix.
http://code.google.com/appengine/docs/python/datastore/queriesandindexes.html
maybe this could do the trick ;)
Altough App Engine does not support LIKE queries, have a look at the properties ListProperty and StringListProperty. When an equality test is done on these properties, the test will actually be applied on all list members, e.g., list_property = value tests if the value appears anywhere in the list.
Sometimes this feature might be used as a workaround to the lack of LIKE queries. For instance, it makes it possible to do simple text search, as described on this post.
You need to use search service to perform full text search queries similar to SQL LIKE.
Gaelyk provides domain specific language to perform more user friendly search queries. For example following snippet will find first ten books sorted from the latest ones with title containing fern
and the genre exactly matching thriller:
def documents = search.search {
select all from books
sort desc by published, SearchApiLimits.MINIMUM_DATE_VALUE
where title =~ 'fern'
and genre = 'thriller'
limit 10
}
Like is written as Groovy's match operator =~.
It supports functions such as distance(geopoint(lat, lon), location) as well.
App engine launched a general-purpose full text search service in version 1.7.0 that supports the datastore.
Details in the announcement.
More information on how to use this: https://cloud.google.com/appengine/training/fts_intro/lesson2
Have a look at Objectify here , it is like a Datastore access API. There is a FAQ with this question specifically, here is the answer
How do I do a like query (LIKE "foo%")
You can do something like a startWith, or endWith if you reverse the order when stored and searched. You do a range query with the starting value you want, and a value just above the one you want.
String start = "foo";
... = ofy.query(MyEntity.class).filter("field >=", start).filter("field <", start + "\uFFFD");
Just follow here:
init.py#354">http://code.google.com/p/googleappengine/source/browse/trunk/python/google/appengine/ext/search/init.py#354
It works!
class Article(search.SearchableModel):
text = db.TextProperty()
...
article = Article(text=...)
article.save()
To search the full text index, use the SearchableModel.all() method to get an
instance of SearchableModel.Query, which subclasses db.Query. Use its search()
method to provide a search query, in addition to any other filters or sort
orders, e.g.:
query = article.all().search('a search query').filter(...).order(...)
I tested this with GAE Datastore low-level Java API. Me and works perfectly
Query q = new Query(Directorio.class.getSimpleName());
Filter filterNombreGreater = new FilterPredicate("nombre", FilterOperator.GREATER_THAN_OR_EQUAL, query);
Filter filterNombreLess = new FilterPredicate("nombre", FilterOperator.LESS_THAN, query+"\uFFFD");
Filter filterNombre = CompositeFilterOperator.and(filterNombreGreater, filterNombreLess);
q.setFilter(filter);
In general, even though this is an old post, a way to produce a 'LIKE' or 'ILIKE' is to gather all results from a '>=' query, then loop results in python (or Java) for elements containing what you're looking for.
Let's say you want to filter users given a q='luigi'
users = []
qry = self.user_model.query(ndb.OR(self.user_model.name >= q.lower(),self.user_model.email >= q.lower(),self.user_model.username >= q.lower()))
for _qry in qry:
if q.lower() in _qry.name.lower() or q.lower() in _qry.email.lower() or q.lower() in _qry.username.lower():
users.append(_qry)
It is not possible to do a LIKE search on datastore app engine, how ever creating an Arraylist would do the trick if you need to search a word in a string.
#Index
public ArrayList<String> searchName;
and then to search in the index using objectify.
List<Profiles> list1 = ofy().load().type(Profiles.class).filter("searchName =",search).list();
and this will give you a list with all the items that contain the world you did on the search
If the LIKE '%text%' always compares to a word or a few (think permutations) and your data changes slowly (slowly means that it's not prohibitively expensive - both price-wise and performance-wise - to create and updates indexes) then Relation Index Entity (RIE) may be the answer.
Yes, you will have to build additional datastore entity and populate it appropriately. Yes, there are some constraints that you will have to play around (one is 5000 limit on the length of list property in GAE datastore). But the resulting searches are lightning fast.
For details see my RIE with Java and Ojbectify and RIE with Python posts.
"Like" is often uses as a poor-man's substitute for text search. For text search, it is possible to use Whoosh-AppEngine.