I have a website that operates similarly to many freelancing websites where people can make bids. Its become painfully slow in recent weeks and I used query monitor to find out the issue is likely over 140,000 posts that were build up over the last 5 years. Below is a query that takes 36 seconds (from query monitor)
...
SELECT wp_4_posts.ID
FROM wp_4_posts
WHERE 1=1
AND wp_4_posts.post_parent = 427941
AND wp_4_posts.post_author IN (1)
AND wp_4_posts.post_type = 'bid'
AND ((wp_4_posts.post_status = 'publish'))
ORDER BY wp_4_posts.post_date DESC
LIMIT 0, 5 +
WP_Query->get_posts()
...
I'm wondering how I can:
Delete any post of type "bid" that are in draft status
Delete any post of type "bid" that are in published status but made before 2020
The best solution for your is Bulk delete plugin, this plugin will allow you to delete a specific post type, specific post status, and you can do the operation in a bundle, like 50 posts at a time, or 200.
https://wordpress.org/plugins/wp-bulk-delete/
Related
Can someone help me figure out how I can retrieve all tickets? I read online and saw that there's no API to do this yet? I also read that i can write some sql code to retrieve them?
My objective is: Check OSticket to see if the ticket with the same subject is created more than 3 times, then to basically alert me ( for now it can just be a message in Powershell that says it, as I'm scripting in PS).
For that I need to retrieve all tickets in the OSticketDB. Since I just have it locally for now, I have a sql DB setup but I don't see something along the lines of ost_tickets? Not sure how I can retrieve tickets that have been duplicates from same subject.
I'm not sure I understand your question correctly. But here is SQL query, that will return all tickets, where subject has occurred more than 3 times.
SELECT
cdata.ticket_id,
cdata.subject,
ticket.number,
subjectstable.subjectcount
FROM
osticketdb.ost_ticket AS ticket
INNER JOIN osticketdb.ost_ticket__cdata AS cdata ON ticket.ticket_id = cdata.ticket_id
INNER JOIN
(SELECT subject, COUNT(*) as subjectcount FROM osticketdb.ost_ticket__cdata GROUP BY subject) AS subjectstable
ON subjectstable.subject = cdata.subject
WHERE subjectstable.subjectcount > 3
I'm having a quick issue I could use an opinion on. I'm attempting to write a MySQL query that pulls all the messages from a conversation that is exclusively between two users.
I need to be able to pull messages sent by 'user1' that are sent to 'user2', and messages sent by 'user2' that are sent to 'user1'.
I've dabbled a bit and I've currently got the 4 conditions needed for my query to execute (see below). I've been trying to work out what way to structure it to get the specific data I need though.
SELECT privatemessage_message, privatemessage_time_created, privatemessage_sent_by, privatemessage_sent_to
FROM tbl_privatemessages
WHERE privatemessage_sent_by = 1
OR privatemessage_sent_by = 2
OR privatemessage_sent_to = 1
OR privatemessage_sent_to = 2
ORDER BY privatemessage_time_created ASC
For context :
This is going to be used within a PHP MySQL website with AJAX being used for the private messaging. I'm fine withthem sides of it, but this particular SQL query is a nuisance.
Any help is greatly appreciated :)
You need to use AND to combine the sender and recipient, and OR to combine the different directions.
SELECT privatemessage_message, privatemessage_time_created, privatemessage_sent_by, privatemessage_sent_to
FROM tbl_privatemessages
WHERE (privatemessage_sent_by = 1 AND privatemessage_sent_to = 2)
OR (privatemessage_sent_to = 1 AND privatemessage_sent_by = 2)
ORDER BY privatemessage_time_created ASC
This query creates an export for UPS from the deliveries history:
select 'key'
, ACC.Name
, CON.FullName
, CON.Phone
, ADR.AddressLine1
, ADR.AddressLine2
, ADR.AddressLine3
, ACC.Postcode
, ADR.City
, ADR.Country
, ACC.Code
, DEL.DeliveryNumber
, CON.Email
, case
when CON.Email is not null
then 'Y'
else 'N'
end
Ship_Not_Option
, 'Y' Ship_Not
, 'ABCDEFG' Description_Goods
, '1' numberofpkgs
, 'PP' billing
, 'CP' pkgstype
, 'ST' service
, '1' weight
, null Shippernr
from ExactOnlineREST..GoodsDeliveries del
join ExactOnlineREST..Accounts acc
on ACC.ID = del.DeliveryAccount
join ExactOnlineREST..Addresses ADR
on ADR.ID = DEL.DeliveryAddress
join ExactOnlineREST..Contacts CON
on CON.ID = DEL.DeliveryContact
where DeliveryDate between $P{P_SHIPDATE_FROM} and $P{P_SHIPDATE_TO}
order
by DEL.DeliveryNumber
It takes many minutes to run. The number of deliveries and accounts grows with several hundreds each day. Addresses and contacts are mostly 1:1 with accounts. How can this query be optimized for speed in Invantive Control for Excel?
Probably this query is run at most once every day, since the deliverydate does not contain time. Therefore, the number of rows selected from ExactOnlineREST..GoodsDeliveries is several hundreds. Based upon the statistics given, the number of accounts, deliveryaddresses and contacts is also approximately several hundreds.
Normally, such a query would be optimized by a solution such as Exact Online query with joins runs more than 15 minutes, but that solution will not work here: the third value of a join_set(soe, orderid, 100) is the maximum number of rows on the left-hand side to be used with index joins. At this moment, the maximum number on the left-hand side is something like 125, based upon constraints on the URL length for OData requests to Exact Online. Please remember the actual OData query is a GET using an URL, not a POST with unlimited size for the filter.
The alternatives are:
Split volume
Data Cache
Data Replicator
Have SQL engine or Exact Online adapted :-)
Split Volume
In a separate query select the eligible GoodsDeliveries and put them in an in-memory or database table using for instance:
create or replace table gdy#inmemorystorage as select ... from ...
Then create a temporary table per 100 or similar rows such as:
create or replace table gdysubpartition1#inmemorystorage as select ... from ... where rowidx$ between 0 and 99
... etc for 100, 200, 300, 400, 500
And then run the query several times, each time with a different gdysubpartition1..gdysubpartition5 instead of the original from ExactOnlineREST..GoodsDeliveries.
Of course, you can also avoid the use of intermediate tables by using an inline view like:
from (select * from goodsdeliveries where date... limit 100)
or alike.
Data Cache
When you run the query multiple times per day (unlikely, but I don't know), you might want to cache the Accounts in a relational database and update it every day.
You can also use a 'local memorize results clipboard andlocal save results clipboard to to save the last results to a file manually and later restore them usinglocal load results clipboard from ...andlocal insert results clipboard in table . And maybe theninsert into from exactonlinerest..accounts where datecreated > trunc(sysdate)`.
Data Replicator
With Data Replicator enabled, you can have replicas created and maintained automatically within an on-premise or cloud relational database for Exact Online API entities. For low latency, you will need to enable the Exact webhooks.
Have SQL Engine or Exact adapted
You can also register a request to have the SQL engine to allow higher number in the join_set hint, which would require addressing the EOL APIs in another way. Or register a request at Exact to also allow POST requests to the API with the filter in the body.
Wow, makes your head spin!
I am about to start a project, and although my mySql is OK, I can't get my head around what required for this:
I have a table of web addresses.
id,url
1,http://www.url1.com
2,http://www.url2.com
3,http://www.url3.com
4,http://www.url4.com
I have a table of users.
id,name
1,fred bloggs
2,john bloggs
3,amy bloggs
I have a table of categories.
id,name
1,science
2,tech
3,adult
4,stackoverflow
I have a table of categories the user likes as numerical ref relating to the category unique ref. For example:
user,category
1,4
1,6
1,7
1,10
2,3
2,4
3,5
.
.
.
I have a table of scores relating to each website address. When a user visits one of these sites and says they like it, it's stored like so:
url_ref,category
4,2
4,3
4,6
4,2
4,3
5,2
5,3
.
.
.
So based on the above data, URL 4 would score (in it's own right) as follows: 2=2 3=2 6=1
What I was hoping to do was pick out a random URL from over 2,000,000 records based on the current users interests.
So if the logged in user likes categories 1,2,3 then I would like to ORDER BY a score generated based on their interest.
If the logged in user likes categories 2 3 and 6 then the total score would be 5. However, if the current logged in user only like categories 2 and 6, the URL score would be 3. So the order by would be in context of the logged in users interests.
Think of stumbleupon.
I was thinking of using a set of VIEWS to help with sub queries.
I'm guessing that all 2,000,000 records will need to be looked at and based on the id of the url it will look to see what scores it has based on each selected category of the current user.
So we need to know the user ID and this gets passed into the query as a constant from the start.
Ain't got a clue!
Chris Denman
What I was hoping to do was pick out a random URL from over 2,000,000 records based on the current users interests.
This screams for predictive modeling, something you probably wouldn't be able to pull off in the database. Basically, you'd want to precalculate your score for a given interest (or more likely set of interests) / URL combination, and then query based on the precalculated values. You'd most likely be best off doing this in application code somewhere.
Since you're trying to guess whether a user will like or dislike a link based on what you know about them, Bayes seems like a good starting point (sorry for the wikipedia link, but without knowing your programming language this is probably the best place to start): Naive Bayes Classifier
edit
The basic idea here is that you continually run your precalculation process, and once you have enough data you can try to distill it to a simple formula that you can use in your query. As you collect more data, you continue to run the precalculation process and use the expanded results to refine your formula. This gets really interesting if you have the means to suggest a link, then find out whether the user liked it or not, as you can use this feedback loop really improve the prediction algorithm (have a read on machine learning, particularly genetic algorithms, for more on this)
I did this in the end:
$dbh = new NewSys::mySqlAccess("xxxxxxxxxx","xxxxxxxxxx","xxxxxxxxx","localhost");
$icat{1}='animals pets';
$icat{2}='gadget addict';
$icat{3}='games online play';
$icat{4}='painting art';
$icat{5}='graphic designer design';
$icat{6}='philosophy';
$icat{7}='strange unusual bizarre';
$icat{8}='health fitness';
$icat{9}='photography photographer';
$icat{10}='reading books';
$icat{11}='humour humor comedy comedian funny';
$icat{12}='psychology psychologist';
$icat{13}='cartoons cartoonist';
$icat{14}='internet technology';
$icat{15}='science scientist';
$icat{16}='clothing fashion';
$icat{17}='movies movie latest';
$icat{18}="\"self improvement\"";
$icat{19}='drawing art';
$icat{20}='latest band member';
$icat{21}='shop prices';
$icat{22}='recipe recipes food';
$icat{23}='mythology';
$icat{24}='holiday resorts destinations';
$icat{25}="(rude words)";
$icat{26}="www website";
$dbh->Sql("DELETE FROM precalc WHERE member = '$fdat{cred_id}'");
$dbh->Sql("SELECT * FROM prefs WHERE member = '$fdat{cred_id}'");
#chos=();
while($dbh->FetchRow()){
$cat=$dbh->Data('category');
$cats{$cat}='#';
}
foreach $cat (keys %cats){
push #chos,"\'$cat\'";
push #strings,$icat{$cat};
}
$sqll=join("\,",#chos);
$words=join(" ",#strings);
$dbh->Sql("select users.id,users.url,IFNULL((select sum(scoretot.scr) from scoretot where scoretot.id = users.id and scoretot.category IN \($sqll\)),0) as score from users WHERE MATCH (description,lasttweet) AGAINST ('$words' IN BOOLEAN MODE) AND IFNULL((SELECT ref FROM visited WHERE member = '$fdat{cred_id}' AND user = users.id LIMIT 1),0) = 0 ORDER BY score DESC limit 30");
$cnt=0;
while($dbh->FetchRow()){
$id=$dbh->Data('id');
$url=$dbh->Data('url');
$score=$dbh->Data('score');
$dbh2->Sql("INSERT INTO precalc (member,user,url,score) VALUES ('$fdat{cred_id}','$id','$url','$score')");
$cnt++;
}
I came up with this answer about three months ago, and just cannot read it. So sorry, I can't explain how it finally worked, but it managed to query 2 million websites and choose one based on the history of a users past votes on other sites.
Once I got it working, I moved on to another problem!
http://www.staggerupon.com is where it all happens!
Chris
I have a site with about 30,000 members to which I'm adding a functionality that involves sending a random message from a pool of 40 possible messages. Members can never receive the same message twice.
One table contains the 40 messages and another table maps the many-to-many relationship between messages and members.
A cron script runs daily, selects a member from the 30,000, selects a message from the 40 and then checks to see if this message has been sent to this user before. If not, it sends the message. If yes, it runs the query again until it finds a message that has not yet been received by this member.
What I'm worried about now is that this m-m table will become very big: at 30,000 members and 40 messages we already have 1.2 million rows through which we have to search to find a message that has not yet been sent.
Is this a case for denormalisation? In the members table I could add 40 columns (message_1, message_2 ... message_40) in which a 1 flag is added each time a message is sent. If I'm not mistaken, this would make the queries in the cron script run much faster
?
I know that doesn't answer your original question, but wouldn't it be way faster if you selected all the messages that weren't yet sent to a user and then select one of those randomly?
See this pseudo-mysql here:
SELECT
CONCAT_WS(',', messages.ids) unsent_messages,
user.id user
FROM
messages,
user
WHERE
messages.id NOT IN (
SELECT
id
FROM
sent_messages
WHERE
user.id = sent_messages.user
)
GROUP BY ids
You could also append the id of the sent messages to a varchar-field in the members-table.
Despite of good manners, this would make it easily possible to use one statement to get a message that has not been sent yet for a specific member.
Just like this (if you surround the ids with '-')
SELECT message.id
FROM member, message
WHERE member.id = 2321
AND member.sentmessages NOT LIKE '%-' && id && '-%'
1.2 M rows # 8 bytes (+ overhead) per row is not a lot. It's so small I wouldn't even bet it needs indexing (but of course you should do it).
Normalization reduces redundancy and it is what you'll do if you have large amount of data which seems to be your case. You need not denormalize. Let there be an M-to-M table between members and messages.
You can archive the old data as your M-to-M data increases. I don't even see any conflicts because your cron job runs daily for this task and accounts only for the data for the current day. So you can archive M-to-M table data every week.
I believe there will be maintenance issue if you denormalize by adding additional coloumns to members table. I don't recommend the same. Archiving of old data can save you from trouble.
You could store only available (unsent) messages. This implies extra maintenance when you add or remove members or message types (nothing that can't be automated with foreign keys and triggers) but simplifies delivery: pick a random line from each user, send the message and remove the line. Also, your database will get smaller as messages get sent ;-)
You can achieve the effect of sending random messages by preallocating the random string in your m-m table and a pointer to the offset of the last message sent.
In more detail, create a table MemberMessages with columns
memberId,
messageIdList char(80) or varchar ,
lastMessage int,
primary key is memberId.
Pseudo-code for the cron job then looks like this...
ONE. Select next message for a member. If no row exists in MemberMessages for this member, go to step TWO. The sql to select next message looks like
select substr(messageIdList, 2*lastMessage + 1, 2) as nextMessageId
from MemberMessages
where member_id = ?
send the message identified by nextMessageId
then update lastMessage incrementing by 1, unless you have reached 39 in which case reset it to zero.
update MemberMessages
set lastMessage = MOD(lastMessage + 1, 40)
where member_id = ?
TWO. Create a random list of messageIds as a String of couplets like 2117390740... This is your random list of message IDs as an 80 char String. Insert a row to MemberMessages for your member_id setting message_id_list to your 80 char String and set last_message to 1.
Send the message identified by the first couplet from the list to the member.
You can create a kind of queue / heap.
ReceivedMessages
UserId
MessageId
then:
Pick up a member and select message to send:
SELECT * FROM Messages WHERE MessageId NOT IN (SELECT MessageId FROM ReceivedMessages WHERE UserId = #UserId) LIMIT 1
then insert MessageId and UserId to ReceivedMessages
and do send logic here
I hope that helps.
There are potential easier ways to do this, depending on how random you want "random" to be.
Consider that at the beginning of the day you shuffle an array A, [0..39] which describes the order of the messages to be sent to users today.
Also, consider that you have at most 40 Cron jobs, which are used to send messages to the users. Given the Nth cron job, and ID the selected user ID, numeric, you can choose M, the index of the message to send:
M = (A[N] + ID) % 40.
This way, a given ID would not receive the same message twice in the same day (because A[N] would be different), and two randomly selected users have a 1/40 chance of receiving the same message. If you want more "randomness" you can potentially use multiple arrays.