This fixes a bug where if you were narrowed to a search and received
a new message that belonged in that search, the message would appear
to have an empty subject and content.
(imported from commit fe1dbf584d3659d57c5b70c7eb45cb22bbc9732f)
Previously, we were having this problem where:
* You narrow to something
* That causes message_list.js:process_collapsing to run on all of the
elements in the view, which changes some of their sizes
* That causes the pane to scroll and either push the content up or
down, depending (since stuff on top of where you were is now a
different size)
* That triggers keep_pointer_in_view, which moves your pointer
Moving process_collapsing into narrow.activate doesn't obviously
fix any of this, but it does seem to mitigate the issue a bit.
In particular, we (a) process it less frequently, and (b) process it
immediately after we show the narrowed view table, which seems to
reduce the raciness of the overall experience.
This does, however, introduce a regression:
* If you receive a long message when you're on
#settings, e.g., and then go back to Home,
the message does not properly get a [More] appended
to it.
(imported from commit b1440d656cc7b71eca8af736f2f7b3aa7e0cca14)
This can be useful for debugging what sort of narrow is happening in
addition to the URI decoding bug we're currently experiencing.
(imported from commit 0cb55fec4ac1afa986c747eb79236b4300c9e636)
This post-commit hook depends on pysvn. After a transaction is completed,
a Humbug is sent to a configurable stream with the repo modified, actor,
and commit message.
(imported from commit 75cab82d5fe993ea7c4c05be07a7b61e770aff81)
This shouldn't have any effect in normal realms, but for realms like
mit.edu that have large numbers of inactive streams, it will sort all
the streams that have had a recent message at the top (aka those that
aren't effectively inactive).
(imported from commit 027ce258d04b6fd58705e49f769dec7e0639bb38)
Previously we used the value of gafyd_name in forms, which means that if
it was undefined we'd end up with a string literal "None" being passed to
the registration form by the confirmation redirector.
(imported from commit c8fbb749bb793c8e927e86603ce196bf810f3f6a)
We HTML-escape the subject in Postgres to avoid a server round-trip.
Unlike the rendered_content, which is already escaped and cached on
zephyr_message, we normally escape subjects client-side. Escaping in
Django would require fetching the messages that match the query,
escaping the subjects, and then making a second query to Postgres to
insert the markup. We could instead fetch the messages with subjects
marked up using non-HTML (some unique string) that is later converted
into the correct markup either in Django or client-side, but then the
escaping problem would just be with some random string instead of
HTML. Since the function is pretty simple, doing the escaping in
Postgres itself is the least painful option.
(imported from commit 004931d8e496697c18650aee97b1a74c55a04cb2)
In addition to changing the trigger that updates
zephyr_message.search_tsvector to use our new text search
configuration, it also now builds the tsvector on rendered_content
instead of content and fires on update of only the subject or
rendered_content columns.
This migration is expected to take a long time. The
checkpoint_segments parameter in postgresql.conf should be
temporarily raised (probably to 32) while it is running.
(imported from commit 4535438bb33ce1db2a74ecbe91efc52afdb568f1)
Text search was not that great partially because Postgres wasn't
using a ispell dictionary (Postgres term) before. We now pull in
Hunspell and use its dictionary and affix rules.
It is Ok to run with this new configuration before updating our full
text column and index that will be coming in the next few commits.
Manual steps for deploy:
1) On both postgres0 and postgres1 (both before moving on to step 2),
install the hunspell-en-us package
2) On staging, run migration 0022
3) On both postgres0 and postgres1, copy the appropriate postgresql.conf
file over
4) On both postgres0 and postgres1, run `pg_ctlcluster 9.1 main reload`
(imported from commit 706bf0f6ecc46c712cea10b73c34fd9d1dfd4767)
There's still a lot to do here. For example, the external code
should probably go through the new Filter object directly instead of
indirectly through the narrow module.
(imported from commit 22dcd31cdebd51453f1658af52a4432b2fe7a4cb)
In the case where we're getting old messages for a narrowed view, the
anchor message id might not actually be in the result set so there's
no reason to fetch an extra message.
(imported from commit e610d1f2cb95be3ff9fce6dc95e40c560bc5bf84)
In particular, I added absolute positioning and hidden overflow,
which ensures that if an element has a persistent min-width
(like a file input field apparently does), it doesn't affect its
parent.
(imported from commit 72e7a5bee2775fb6f229899ba849292eee76aa4a)
In repeated trials, the initial data fetch used to take about 1100ms.
In practice, it was often taking >2000ms, probably due to caching
effects. This commit cuts the time down to about 300ms in repeated
trials.
Note that the semantics are changed slightly in that we may no longer
get exactly 25000 messages. However, holes in the message_id
sequence are currently very rare or non-existent so this shouldn't be
a problem and we don't care about the exact number of messages
anyway.
I believe the problem was that the query planner was unable to
effectively use the LIMIT clause to figure out that only a small
subset of zephyr_message was going to be needed. Thus, it planned
for operating on the entire table and decided it could not use a more
efficient plan because work_mem, although large, would not be large
enough to execute the query over all of zephyr_message.
The original query was:
SELECT "zephyr_message"."id", "zephyr_message"."sender_id", "zephyr_message"."recipient_id", "zephyr_message"."subject", "zephyr_message"."content", "zephyr_message"."rendered_content", "zephyr_message"."rendered_content_version", "zephyr_message"."pub_date", "zephyr_message"."sending_client_id", "zephyr_userprofile"."id", "zephyr_userprofile"."password", "zephyr_userprofile"."last_login", "zephyr_userprofile"."email", "zephyr_userprofile"."is_staff", "zephyr_userprofile"."is_active", "zephyr_userprofile"."date_joined", "zephyr_userprofile"."full_name", "zephyr_userprofile"."short_name", "zephyr_userprofile"."pointer", "zephyr_userprofile"."last_pointer_updater", "zephyr_userprofile"."realm_id", "zephyr_userprofile"."api_key", "zephyr_userprofile"."enable_desktop_notifications", "zephyr_userprofile"."enter_sends", "zephyr_userprofile"."tutorial_status", "zephyr_realm"."id", "zephyr_realm"."domain", "zephyr_realm"."restricted_to_domain", "zephyr_recipient"."id", "zephyr_recipient"."type_id", "zephyr_recipient"."type", "zephyr_client"."id", "zephyr_client"."name" FROM "zephyr_message" INNER JOIN "zephyr_userprofile" ON ( "zephyr_message"."sender_id" = "zephyr_userprofile"."id" ) INNER JOIN "zephyr_realm" ON ( "zephyr_userprofile"."realm_id" = "zephyr_realm"."id" ) INNER JOIN "zephyr_recipient" ON ( "zephyr_message"."recipient_id" = "zephyr_recipient"."id" ) INNER JOIN "zephyr_client" ON ( "zephyr_message"."sending_client_id" = "zephyr_client"."id" ) ORDER BY "zephyr_message"."id" DESC LIMIT 25000;
with query plan:
Limit (cost=0.00..27120.95 rows=25000 width=362) (actual time=0.051..1121.282 rows=25000 loops=1)
-> Nested Loop (cost=0.00..5330872.99 rows=4913981 width=362) (actual time=0.048..1081.014 rows=25000 loops=1)
-> Nested Loop (cost=0.00..3932643.31 rows=4913981 width=344) (actual time=0.042..926.398 rows=25000 loops=1)
-> Nested Loop (cost=0.00..2550275.29 rows=4913981 width=334) (actual time=0.035..752.524 rows=25000 loops=1)
Join Filter: (zephyr_message.sending_client_id = zephyr_client.id)
-> Nested Loop (cost=0.00..1739467.29 rows=4913981 width=320) (actual time=0.024..217.348 rows=25000 loops=1)
-> Index Scan Backward using zephyr_message_pkey on zephyr_message (cost=0.00..362510.09 rows=4913981 width=156) (actual time=0.014..42.097 rows=25000 loops=1)
-> Index Scan using zephyr_userprofile_pkey on zephyr_userprofile (cost=0.00..0.27 rows=1 width=164) (actual time=0.003..0.004 rows=1 loops=25000)
Index Cond: (id = zephyr_message.sender_id)
-> Materialize (cost=0.00..1.17 rows=11 width=14) (actual time=0.001..0.010 rows=11 loops=25000)
-> Seq Scan on zephyr_client (cost=0.00..1.11 rows=11 width=14) (actual time=0.002..0.010 rows=11 loops=1)
-> Index Scan using zephyr_recipient_pkey on zephyr_recipient (cost=0.00..0.27 rows=1 width=10) (actual time=0.002..0.003 rows=1 loops=25000)
Index Cond: (id = zephyr_message.recipient_id)
-> Index Scan using zephyr_realm_pkey on zephyr_realm (cost=0.00..0.27 rows=1 width=18) (actual time=0.002..0.003 rows=1 loops=25000)
Index Cond: (id = zephyr_userprofile.realm_id)
Total runtime: 1141.408 ms
In the new code, we do two queries:
SELECT "zephyr_message"."id" FROM "zephyr_message" ORDER BY "zephyr_message"."id" DESC LIMIT 1
followed by:
SELECT "zephyr_message"."id", "zephyr_message"."sender_id", "zephyr_message"."recipient_id", "zephyr_message"."subject", "zephyr_message"."content", "zephyr_message"."rendered_content", "zephyr_message"."rendered_content_version", "zephyr_message"."pub_date", "zephyr_message"."sending_client_id", "zephyr_userprofile"."id", "zephyr_userprofile"."password", "zephyr_userprofile"."last_login", "zephyr_userprofile"."email", "zephyr_userprofile"."is_staff", "zephyr_userprofile"."is_active", "zephyr_userprofile"."date_joined", "zephyr_userprofile"."full_name", "zephyr_userprofile"."short_name", "zephyr_userprofile"."pointer", "zephyr_userprofile"."last_pointer_updater", "zephyr_userprofile"."realm_id", "zephyr_userprofile"."api_key", "zephyr_userprofile"."enable_desktop_notifications", "zephyr_userprofile"."enter_sends", "zephyr_userprofile"."tutorial_status", "zephyr_realm"."id", "zephyr_realm"."domain", "zephyr_realm"."restricted_to_domain", "zephyr_recipient"."id", "zephyr_recipient"."type_id", "zephyr_recipient"."type", "zephyr_client"."id", "zephyr_client"."name" FROM "zephyr_message" INNER JOIN "zephyr_userprofile" ON ( "zephyr_message"."sender_id" = "zephyr_userprofile"."id" ) INNER JOIN "zephyr_realm" ON ( "zephyr_userprofile"."realm_id" = "zephyr_realm"."id" ) INNER JOIN "zephyr_recipient" ON ( "zephyr_message"."recipient_id" = "zephyr_recipient"."id" ) INNER JOIN "zephyr_client" ON ( "zephyr_message"."sending_client_id" = "zephyr_client"."id" ) WHERE "zephyr_message"."id" > 4941883
with the message id filled in as the result of the first query. The
new query differs from the original only in that its ORDER BY and
LIMIT clauses are replaced by a WHERE clause. The second query has
query plan:
Hash Join (cost=709.30..28048.18 rows=20544 width=365) (actual time=41.678..279.261 rows=25041 loops=1)
Hash Cond: (zephyr_message.recipient_id = zephyr_recipient.id)
-> Hash Join (cost=102.98..27056.66 rows=20544 width=355) (actual time=3.686..190.730 rows=25041 loops=1)
Hash Cond: (zephyr_message.sending_client_id = zephyr_client.id)
-> Hash Join (cost=101.73..26772.94 rows=20544 width=341) (actual time=3.649..143.695 rows=25041 loops=1)
Hash Cond: (zephyr_userprofile.realm_id = zephyr_realm.id)
-> Hash Join (cost=99.99..26488.71 rows=20544 width=323) (actual time=3.578..96.746 rows=25041 loops=1)
Hash Cond: (zephyr_message.sender_id = zephyr_userprofile.id)
-> Index Scan using zephyr_message_pkey on zephyr_message (cost=0.00..26106.24 rows=20544 width=159) (actual time=0.017..41.980 rows=25041 loops=1)
Index Cond: (id > 4941883)
-> Hash (cost=83.33..83.33 rows=1333 width=164) (actual time=3.548..3.548 rows=1333 loops=1)
Buckets: 1024 Batches: 1 Memory Usage: 275kB
-> Seq Scan on zephyr_userprofile (cost=0.00..83.33 rows=1333 width=164) (actual time=0.006..1.646 rows=1333 loops=1)
-> Hash (cost=1.33..1.33 rows=33 width=18) (actual time=0.064..0.064 rows=33 loops=1)
Buckets: 1024 Batches: 1 Memory Usage: 2kB
-> Seq Scan on zephyr_realm (cost=0.00..1.33 rows=33 width=18) (actual time=0.003..0.033 rows=33 loops=1)
-> Hash (cost=1.11..1.11 rows=11 width=14) (actual time=0.027..0.027 rows=11 loops=1)
Buckets: 1024 Batches: 1 Memory Usage: 1kB
-> Seq Scan on zephyr_client (cost=0.00..1.11 rows=11 width=14) (actual time=0.003..0.013 rows=11 loops=1)
-> Hash (cost=335.03..335.03 rows=21703 width=10) (actual time=37.974..37.974 rows=21761 loops=1)
Buckets: 4096 Batches: 1 Memory Usage: 893kB
-> Seq Scan on zephyr_recipient (cost=0.00..335.03 rows=21703 width=10) (actual time=0.004..18.443 rows=21761 loops=1)
Total runtime: 299.300 ms
(imported from commit b2a70cccc47be7970df407c6be00eccd2e8be82a)
Jessica McKellar
Zev Benjamin
Steve Howell
Leo Franchi
Waseem Daher
Tim Abbott
Luke Faraone
Allen Rabinovich
Jeff Arnold