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/* This Source Code Form is subject to the terms of the Mozilla Public
* License, v. 2.0. If a copy of the MPL was not distributed with this
const lazy = {};
ChromeUtils.defineESModuleGetters(lazy, {
NewTabUtils: "resource://gre/modules/NewTabUtils.sys.mjs",
thompsonSampleSort: "chrome://global/content/ml/ThomSample.sys.mjs",
sortKeysValues: "chrome://global/content/ml/ThomSample.sys.mjs",
});
const SHORTCUT_TABLE = "moz_newtab_shortcuts_interaction";
const PLACES_TABLE = "moz_places";
/**
* Get clicks and impressions for sites in topsites array
*
* @param {object[]} topsites Array of topsites objects
* @param {string} table Table for shortcuts interactions
* @param {string} placeTable moz_places table
* @returns {clicks: [number[], impressions: number[]]} Clicks and impressions for each site in topsites
*/
async function fetchShortcutInteractions(topsites, table, placeTable) {
if (!topsites.length) {
// Return empty clicks and impressions arrays
return [[], []];
}
const guidList = topsites.map(site => site.guid);
const valuesClause = guidList
.map(guid => `('${guid.replace(/'/g, "''")}')`)
.join(", ");
// Only get records in the last month!
// Join no places table to map guid to place_id
const sql = `
WITH input_keys(guid) AS (
VALUES ${valuesClause}
),
place_ids AS (
SELECT input_keys.guid, ${placeTable}.id AS place_id
FROM input_keys
JOIN ${placeTable} ON ${placeTable}.guid = input_keys.guid
)
SELECT
place_ids.guid AS key,
COALESCE(SUM(${table}.event_type), 0) AS total_clicks,
COALESCE(SUM(1 - ${table}.event_type), 0) AS total_impressions
FROM place_ids
LEFT JOIN ${table} ON ${table}.place_id = place_ids.place_id
AND ${table}.timestamp_s >= strftime('%s', 'now', '-2 month')
GROUP BY place_ids.guid;
`;
const { activityStreamProvider } = lazy.NewTabUtils;
const interactions = await activityStreamProvider.executePlacesQuery(sql);
const interactionMap = new Map(
interactions.map(row => {
// Destructure the array into variables
const [key, total_clicks, total_impressions] = row;
return [key, { clicks: total_clicks, impressions: total_impressions }];
})
);
// Rebuild aligned arrays in same order as input
const clicks = guidList.map(guid =>
interactionMap.has(guid) ? interactionMap.get(guid).clicks : 0
);
const impressions = guidList.map(guid =>
interactionMap.has(guid) ? interactionMap.get(guid).impressions : 0
);
return [clicks, impressions];
}
/**
* Scale an array to have min value 0 and max value 1
*
* @param {number[]} arr Array to scale
* @returns {scaled: number[]} Scaled array
*/
function zeroOneScaler(arr) {
const min = Math.min(...arr);
const max = Math.max(...arr);
const range = max - min;
const scaled = arr.map(x => (x - min) / range);
return scaled;
}
function multi_ranker(key_arr, arrs, weights) {
// zero-one scale array, then weight
const scaled_arrs = arrs.map((arr, i) =>
zeroOneScaler(arr).map(num => num * weights[i])
);
// sum over scaled-weighted arrays
const resolved_scores = scaled_arrs.reduce((sum, arr) =>
arr.map((value, i) => sum[i] + value)
);
// sort keys by scores
const [final_keys, final_scores] = lazy.sortKeysValues(
resolved_scores,
key_arr
);
return [final_keys, final_scores];
}
/**
* Apply thompson sampling to topsites array, considers frecency weights
*
* @param {object[]} topsites Array of topsites objects
* @param {number} alpha Positive prior applied to all topsites
* @param {number} beta Negative prior applied to all topsites
* @param {number} thom_weight Number between 0 and 1, weight for thompson sampled scores. Frecency weight will be the compliment
* @returns {combined: object[]} Array of topsites in reranked order
*/
export async function tsampleTopSites(
topsites,
alpha = 1,
beta = 1,
thom_weight = 1.0
) {
// split topsites into two arrays
const [withGuid, withoutGuid] = topsites.reduce(
([withG, withoutG], site) => {
if (site.guid && typeof site.guid === "string") {
withG.push(site);
} else {
withoutG.push(site);
}
return [withG, withoutG];
},
[[], []]
);
// query for interactions
const [clicks, impressions] = await fetchShortcutInteractions(
withGuid,
SHORTCUT_TABLE,
PLACES_TABLE
);
// sample a sorted version of topsites
const ranked_thetas = await lazy.thompsonSampleSort({
key_array: withGuid,
obs_positive: clicks,
obs_negative: impressions,
prior_positive: clicks.map(() => alpha),
prior_negative: impressions.map(() => beta),
do_sort: false,
});
// get frecency from withGUID
const frec_scores = withGuid.map(site => site.frecency);
// rank by frecency and thompson theta
const ranked_scores = multi_ranker(
withGuid,
[frec_scores, ranked_thetas[1]],
[1 - thom_weight, thom_weight]
);
// drop theta from ranked to keep just the keys, combine back
const combined = ranked_scores[0].concat(withoutGuid);
return combined; // returns keys ordered by sampled score
}