151 lines
8.4 KiB
Java
151 lines
8.4 KiB
Java
/*
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* This file is part of Player Analytics (Plan).
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*
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* Plan is free software: you can redistribute it and/or modify
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* it under the terms of the GNU Lesser General Public License v3 as published by
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* the Free Software Foundation, either version 3 of the License, or
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* (at your option) any later version.
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*
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* Plan is distributed in the hope that it will be useful,
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* but WITHOUT ANY WARRANTY; without even the implied warranty of
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* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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* GNU Lesser General Public License for more details.
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*
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* You should have received a copy of the GNU Lesser General Public License
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* along with Plan. If not, see <https://www.gnu.org/licenses/>.
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*/
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package com.djrapitops.plan.delivery.rendering.json.network;
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import com.djrapitops.plan.delivery.formatting.Formatter;
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import com.djrapitops.plan.delivery.formatting.Formatters;
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import com.djrapitops.plan.delivery.rendering.json.Trend;
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import com.djrapitops.plan.settings.config.PlanConfig;
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import com.djrapitops.plan.settings.config.paths.TimeSettings;
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import com.djrapitops.plan.storage.database.DBSystem;
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import com.djrapitops.plan.storage.database.Database;
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import com.djrapitops.plan.storage.database.queries.analysis.NetworkActivityIndexQueries;
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import com.djrapitops.plan.storage.database.queries.analysis.PlayerCountQueries;
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import com.djrapitops.plan.storage.database.queries.objects.SessionQueries;
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import javax.inject.Inject;
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import javax.inject.Singleton;
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import java.util.HashMap;
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import java.util.Map;
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import java.util.concurrent.TimeUnit;
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/**
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* Parses JSON payload for /network-page Playerbase Overview tab.
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*
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* @author Rsl1122
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*/
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@Singleton
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public class NetworkPlayerBaseOverviewJSONParser implements NetworkTabJSONParser<Map<String, Object>> {
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private final PlanConfig config;
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private final DBSystem dbSystem;
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private final Formatter<Long> timeAmount;
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private final Formatter<Double> percentage;
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@Inject
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public NetworkPlayerBaseOverviewJSONParser(
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PlanConfig config,
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DBSystem dbSystem,
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Formatters formatters
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) {
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this.config = config;
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this.dbSystem = dbSystem;
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timeAmount = formatters.timeAmount();
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percentage = formatters.percentage();
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}
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public Map<String, Object> createJSONAsMap() {
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Map<String, Object> serverOverview = new HashMap<>();
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serverOverview.put("trends", createTrendsMap());
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serverOverview.put("insights", createInsightsMap());
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return serverOverview;
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}
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private Map<String, Object> createTrendsMap() {
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Database db = dbSystem.getDatabase();
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long now = System.currentTimeMillis();
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long monthAgo = now - TimeUnit.DAYS.toMillis(30L);
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long twoMonthsAgo = now - TimeUnit.DAYS.toMillis(60L);
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Long playThreshold = config.get(TimeSettings.ACTIVE_PLAY_THRESHOLD);
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Map<String, Object> trends = new HashMap<>();
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Integer playersBefore = db.query(PlayerCountQueries.newPlayerCount(0L, monthAgo));
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Integer playersAfter = db.query(PlayerCountQueries.newPlayerCount(0L, now));
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trends.put("total_players_then", playersBefore);
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trends.put("total_players_now", playersAfter);
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trends.put("total_players_trend", new Trend(playersBefore, playersAfter, false));
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Integer regularBefore = db.query(NetworkActivityIndexQueries.fetchRegularPlayerCount(monthAgo, playThreshold));
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Integer regularAfter = db.query(NetworkActivityIndexQueries.fetchRegularPlayerCount(now, playThreshold));
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trends.put("regular_players_then", regularBefore);
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trends.put("regular_players_now", regularAfter);
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trends.put("regular_players_trend", new Trend(regularBefore, regularAfter, false));
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Long avgPlaytimeBefore = db.query(SessionQueries.averagePlaytimePerPlayer(twoMonthsAgo, monthAgo));
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Long avgPlaytimeAfter = db.query(SessionQueries.averagePlaytimePerPlayer(monthAgo, now));
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trends.put("playtime_avg_then", timeAmount.apply(avgPlaytimeBefore));
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trends.put("playtime_avg_now", timeAmount.apply(avgPlaytimeAfter));
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trends.put("playtime_avg_trend", new Trend(avgPlaytimeBefore, avgPlaytimeAfter, false, timeAmount));
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Long avgAfkBefore = db.query(SessionQueries.averageAfkPerPlayer(twoMonthsAgo, monthAgo));
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Long avgAfkAfter = db.query(SessionQueries.averageAfkPerPlayer(monthAgo, now));
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double afkPercBefore = avgPlaytimeBefore != 0 ? (double) avgAfkBefore / avgPlaytimeBefore : 0;
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double afkPercAfter = avgPlaytimeAfter != 0 ? (double) avgAfkAfter / avgPlaytimeAfter : 0;
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trends.put("afk_then", percentage.apply(afkPercBefore));
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trends.put("afk_now", percentage.apply(afkPercAfter));
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trends.put("afk_trend", new Trend(afkPercBefore, afkPercAfter, Trend.REVERSED, percentage));
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Long avgRegularPlaytimeBefore = db.query(NetworkActivityIndexQueries.averagePlaytimePerRegularPlayer(twoMonthsAgo, monthAgo, playThreshold));
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Long avgRegularPlaytimeAfter = db.query(NetworkActivityIndexQueries.averagePlaytimePerRegularPlayer(monthAgo, now, playThreshold));
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trends.put("regular_playtime_avg_then", timeAmount.apply(avgRegularPlaytimeBefore));
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trends.put("regular_playtime_avg_now", timeAmount.apply(avgRegularPlaytimeAfter));
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trends.put("regular_playtime_avg_trend", new Trend(avgRegularPlaytimeBefore, avgRegularPlaytimeAfter, false, timeAmount));
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Long avgRegularSessionLengthBefore = db.query(NetworkActivityIndexQueries.averageSessionLengthPerRegularPlayer(twoMonthsAgo, monthAgo, playThreshold));
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Long avgRegularSessionLengthAfter = db.query(NetworkActivityIndexQueries.averageSessionLengthPerRegularPlayer(monthAgo, now, playThreshold));
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trends.put("regular_session_avg_then", timeAmount.apply(avgRegularSessionLengthBefore));
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trends.put("regular_session_avg_now", timeAmount.apply(avgRegularSessionLengthAfter));
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trends.put("regular_session_avg_trend", new Trend(avgRegularSessionLengthBefore, avgRegularSessionLengthAfter, false, timeAmount));
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Long avgRegularAfkBefore = db.query(NetworkActivityIndexQueries.averageAFKPerRegularPlayer(twoMonthsAgo, monthAgo, playThreshold));
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Long avgRegularAfkAfter = db.query(NetworkActivityIndexQueries.averageAFKPerRegularPlayer(monthAgo, now, playThreshold));
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double afkRegularPercBefore = avgRegularPlaytimeBefore != 0 ? (double) avgRegularAfkBefore / avgRegularPlaytimeBefore : 0;
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double afkRegularPercAfter = avgRegularPlaytimeAfter != 0 ? (double) avgRegularAfkAfter / avgRegularPlaytimeAfter : 0;
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trends.put("regular_afk_avg_then", percentage.apply(afkRegularPercBefore));
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trends.put("regular_afk_avg_now", percentage.apply(afkRegularPercAfter));
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trends.put("regular_afk_avg_trend", new Trend(afkRegularPercBefore, afkRegularPercAfter, Trend.REVERSED, percentage));
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return trends;
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}
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private Map<String, Object> createInsightsMap() {
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Database db = dbSystem.getDatabase();
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long now = System.currentTimeMillis();
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long halfMonthAgo = now - TimeUnit.DAYS.toMillis(15L);
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long monthAgo = now - TimeUnit.DAYS.toMillis(30L);
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Long playThreshold = config.get(TimeSettings.ACTIVE_PLAY_THRESHOLD);
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Map<String, Object> insights = new HashMap<>();
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int newToRegular = db.query(NetworkActivityIndexQueries.countNewPlayersTurnedRegular(monthAgo, now, playThreshold));
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Integer newToRegularBefore = db.query(NetworkActivityIndexQueries.countNewPlayersTurnedRegular(monthAgo, halfMonthAgo, playThreshold));
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Integer newToRegularAfter = db.query(NetworkActivityIndexQueries.countNewPlayersTurnedRegular(halfMonthAgo, now, playThreshold));
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insights.put("new_to_regular", newToRegular);
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insights.put("new_to_regular_trend", new Trend(newToRegularBefore, newToRegularAfter, false));
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Integer regularToInactive = db.query(NetworkActivityIndexQueries.countRegularPlayersTurnedInactive(monthAgo, now, playThreshold));
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Integer regularToInactiveBefore = db.query(NetworkActivityIndexQueries.countRegularPlayersTurnedInactive(monthAgo, halfMonthAgo, playThreshold));
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Integer regularToInactiveAfter = db.query(NetworkActivityIndexQueries.countRegularPlayersTurnedInactive(halfMonthAgo, now, playThreshold));
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insights.put("regular_to_inactive", regularToInactive);
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insights.put("regular_to_inactive_trend", new Trend(regularToInactiveBefore, regularToInactiveAfter, Trend.REVERSED));
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return insights;
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}
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} |