From d8c6f38cb27c039550255067721ee138b8b69ef5 Mon Sep 17 00:00:00 2001
From: myk bilokonsky <mbilokonsky@gmail.com>
Date: Tue, 11 Apr 2017 19:20:07 +0200
Subject: tweaked documentation, only boost public toots, tweaked algorithm

---
 index.js  | 25 ++++++++++++++++---------
 readme.md | 17 ++++++++++++-----
 2 files changed, 28 insertions(+), 14 deletions(-)

diff --git a/index.js b/index.js
index 121022f..d655618 100644
--- a/index.js
+++ b/index.js
@@ -6,10 +6,13 @@ FROM statuses
 WHERE favourites_count > (
   SELECT avg(favourites_count) 
   FROM statuses 
-  WHERE favourites_count > 1
-  AND created_at > NOW() - INTERVAL '30 days'
+  WHERE 
+    favourites_count > 1
+    AND created_at > NOW() - INTERVAL '30 days'
+    AND visibility = 0
 )
-AND created_at > NOW() - INTERVAL '30 days';`
+AND created_at > NOW() - INTERVAL '5 days'
+AND visibility = 0;`
 
 var config = {
   user: process.env.DB_USER || 'mastodon',
@@ -21,26 +24,23 @@ var config = {
   idleTimeoutMillis: 30000, // how long a client is allowed to remain idle before being closed
 };
 
-// instantiate a new client
+
 var client = new pg.Client(config);
 
 function cycle() {
-  // connect to our database
   client.connect(function (err) {
     if (err) throw err;
 
-    // execute a query on our database
     client.query(query, [], function (err, result) {
       if(err) {
         return console.error('error running query', err);
       }
 
-      boost(result.rows);
-
-      // disconnect the client
       client.end(function (err) {
         if (err) throw err;
       });
+
+      boost(result.rows);
     });
   });
 }
@@ -51,6 +51,11 @@ var M = new mastodon({
 });
 
 var boosted = {};
+
+function clearCache() {
+  boosted = {};
+}
+
 function boost(rows) {
   rows.map(function(row) {
     return row.id;
@@ -75,4 +80,6 @@ function boost(rows) {
 }
 
 cycle();
+// clear that 'cache' daily, 2 seconds before the hour (since cycle runs on the hour)
+setInterval(clearCache, (1000 * 60 * 60 * 24) - 2000); 
 setInterval(cycle, 1000 * 60 * 15);
\ No newline at end of file
diff --git a/readme.md b/readme.md
index 00fba1d..1c9ebae 100644
--- a/readme.md
+++ b/readme.md
@@ -42,17 +42,24 @@ FROM statuses
 WHERE favourites_count > (
   SELECT avg(favourites_count) 
   FROM statuses 
-  WHERE favourites_count > 1
-  AND created_at > NOW() - INTERVAL '30 days'
+  WHERE 
+    favourites_count > 1
+    AND created_at > NOW() - INTERVAL '30 days'
+    AND visibility = 0
 )
-AND created_at > NOW() - INTERVAL '30 days';
+AND created_at > NOW() - INTERVAL '5 days'
+AND visibility = 0;
 ```
+So we do two things here:
 
-It takes an average of all toots with 2 or more favs over the past 30 days. Any toot within that window that has more than that number of favs gets a boost. Note that most toots won't get 2 favs - so this is already filtering out most toots in your instance. The hope is that by averaging what's left and picking the top half we'll end up with a pretty high standard for what gets boosted, but this algorithm will be tweaked over time.
+1. Compute our fav threshold. Grab all public toots that have received more than 1 fav over the past 30 days. Average the fav counts for those toots. This is our threshold.
+2. Find any public toots created within the past five days which have received at least that many favs.
+
+Goal here is that this sets a pretty high bar (favs over 30 days) and applies it to only the past 5 days. It's an aggressive filter, but it's also a sliding window. If you have a bunch of super popular toots on your instance, they'll skew the curve - but only for a month or so, and this will be normalized if you have a lot of activity. Generally things will even out over time.
 
 ## Seriously? You want me to give this thing access to my production database?
 Look, I get it - but how else do you want me to find your top toot in a performant way? I'm not passing any user input into the database, just repeating a static query. I am not, btw, a database expert - I pieced this query together through trial-and-error and if you want to propose an optimization I am all ears.
 
 ## What's next? Can I help?
-I'd love it if I could get some eyes on this - am I SQLing right? Someone wanna PR in a better 'cache' to prevent reboosting the same statuses over and over again? How do y'all feel about that threshold function? Seems like one really popular toot would break the curve...
+I'd love it if I could get some eyes on this - am I SQLing right? How do y'all feel about that threshold function? Are there security issues here?
 
-- 
cgit