feat(syslog): 优化大日志通道并增加异常连续消费兜底
- 128 KiB 及以上日志默认进入大日志 Topic - InfluxDB 原文及达梦大字段超过 256 KiB 时截断保存 - 截断内容追加 HB_XDR_TRUNCATED 标记 - InfluxDB 写入失败时继续执行规则解析和达梦写入 - 未知或系统性异常优先写入普通/大日志 DLT - DLT 写入失败时记录特殊告警并提交 offset,避免阻塞后续消息 - DLT 失败等待时间默认限制为 1 秒 - 增加连续性放行、DLT 成功及失败监控指标 - 更新 Docker Compose、v3 升级文档及相关测试
This commit is contained in:
+37
-3
@@ -23,9 +23,10 @@ import java.util.SortedMap;
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import java.util.TreeMap;
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/**
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* 把当前事实事务的内存聚合结果直接写入小型统计表。
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* 把当前事实事务的内存聚合结果写入同步投影或可靠异步投影入口。
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*
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* <p>调用方必须已经开启事实事务;本类不会新开事务,也不会吞掉任何数据库异常。</p>
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* <p>DIRECT 默认只追加一条批次 Outbox;SHADOW/显式回退仍同步更新统计表。调用方必须
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* 已经开启事实事务,本类不会吞掉任何数据库异常。</p>
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*/
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@Slf4j
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@Service
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@@ -63,6 +64,7 @@ public class DirectStatsProjectionWriter {
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private final StatsWriteModeProvider modeProvider;
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private final DirectStatsWriteMetrics metrics;
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private final StatsMaterializationPublisher materializationPublisher;
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private final StatsProjectionOutboxWriter projectionOutboxWriter;
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@Value("${stats.incremental.read-enabled:false}")
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private boolean readEnabled;
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@@ -91,11 +93,13 @@ public class DirectStatsProjectionWriter {
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public DirectStatsProjectionWriter(JdbcTemplate jdbc,
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StatsWriteModeProvider modeProvider,
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DirectStatsWriteMetrics metrics,
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StatsMaterializationPublisher materializationPublisher) {
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StatsMaterializationPublisher materializationPublisher,
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StatsProjectionOutboxWriter projectionOutboxWriter) {
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this.jdbc = jdbc;
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this.modeProvider = modeProvider;
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this.metrics = metrics;
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this.materializationPublisher = materializationPublisher;
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this.projectionOutboxWriter = projectionOutboxWriter;
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}
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public WriteResult writeStandardizedRows(List<Map<String, Object>> rows) {
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@@ -160,6 +164,8 @@ public class DirectStatsProjectionWriter {
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status.put("today_stats_date_enabled", todayStatsDateEnabled);
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status.put("business_materialization_mode", asynchronousMaterialization()
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? "KAFKA_DIRTY_KEY" : "SYNCHRONOUS");
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status.put("daily_projection_write_mode", asynchronousProjection()
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? "DURABLE_OUTBOX" : "SYNCHRONOUS_MERGE");
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return status;
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}
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@@ -194,6 +200,24 @@ public class DirectStatsProjectionWriter {
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}
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requireTransaction();
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if (asynchronousProjection()) {
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try {
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long outboxStarted = System.nanoTime();
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projectionOutboxWriter.append(StatsProjectionOutboxEvent.fromAccumulator(accumulator));
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long outboxMs = elapsedMs(outboxStarted);
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int deviceGroups = effectiveDeviceEntries(accumulator).size();
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int ruleGroups = effectiveRuleEntries(accumulator).size();
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metrics.recordSuccess(accumulator.getInputRows(), deviceGroups, ruleGroups,
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aggregateMs, outboxMs, 0L);
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return WriteResult.direct(accumulator.getInputRows(), deviceGroups, ruleGroups,
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aggregateMs, outboxMs, 0L);
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} catch (RuntimeException failure) {
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metrics.recordFailure();
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throw new DirectStatsWriteException(
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"统计投影 Outbox 写入失败,事实事务必须整体回滚", failure);
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}
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}
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List<Map.Entry<DirectStatsAccumulator.DailyKey, DirectStatsAccumulator.DeviceDelta>> devices =
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effectiveDeviceEntries(accumulator);
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List<Map.Entry<DirectStatsAccumulator.DailyKey, DirectStatsAccumulator.RuleDelta>> rules =
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@@ -244,6 +268,11 @@ public class DirectStatsProjectionWriter {
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aggregateMs, 0L, 0L);
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}
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requireTransaction();
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// Additive positive/negative changes commute in the serialized projection consumer. This
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// keeps non-normal UPDATE statistics outside the fact transaction as well.
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if (asynchronousProjection()) {
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return write(accumulator, aggregateMs);
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}
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List<DirectStatsAccumulator.DailyKey> keys = new ArrayList<>(accumulator.getDevices().keySet());
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try {
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long mergeStarted = System.nanoTime();
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@@ -408,6 +437,11 @@ public class DirectStatsProjectionWriter {
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&& materializationPublisher.isEnabled();
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}
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private boolean asynchronousProjection() {
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return modeProvider.getMode() == StatsWriteModeProvider.Mode.DIRECT
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&& projectionOutboxWriter != null && projectionOutboxWriter.isEnabled();
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}
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private List<StatsMaterializationCommand> materializationCommands(
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List<Map.Entry<DirectStatsAccumulator.DailyKey, DirectStatsAccumulator.DeviceDelta>> devices,
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List<Map.Entry<DirectStatsAccumulator.DailyKey, DirectStatsAccumulator.RuleDelta>> rules) {
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+89
@@ -0,0 +1,89 @@
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package com.common.service;
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import com.common.entity.SyslogNonNormalMessage;
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import com.common.util.Utf8TextTruncator;
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import org.springframework.beans.factory.annotation.Value;
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import org.springframework.stereotype.Component;
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import javax.annotation.PostConstruct;
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import java.util.Arrays;
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import java.util.Collections;
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import java.util.LinkedHashSet;
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import java.util.Map;
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import java.util.Set;
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import java.util.concurrent.atomic.LongAdder;
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/** 达梦持久化边界的大字段保护;0 表示兼容模式下不限制。 */
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@Component
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public class DmLargeTextLimiter {
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private static final long MIN_ENABLED_LIMIT = 64L;
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@Value("${dm.normal.large-field-max-utf8-bytes:0}")
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private long normalMaxBytes;
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@Value("${dm.normal.large-fields:http_req_body,http_resp_body,http_req_header,http_resp_header,detail,description,cmdline,shell_cmdline,parent_cmdline,mail_message}")
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private String normalFieldsValue;
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@Value("${dm.non-normal.large-field-max-utf8-bytes:0}")
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private long nonNormalMaxBytes;
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private volatile Set<String> normalFields = Collections.emptySet();
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private final LongAdder normalFieldsTruncated = new LongAdder();
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private final LongAdder nonNormalFieldsTruncated = new LongAdder();
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@PostConstruct
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public void validate() {
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validateLimit(normalMaxBytes, "dm.normal.large-field-max-utf8-bytes");
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validateLimit(nonNormalMaxBytes, "dm.non-normal.large-field-max-utf8-bytes");
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Set<String> parsed = new LinkedHashSet<>();
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if (normalFieldsValue != null) {
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Arrays.stream(normalFieldsValue.split(","))
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.map(String::trim).filter(value -> !value.isEmpty()).forEach(parsed::add);
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}
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normalFields = Collections.unmodifiableSet(parsed);
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}
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private static void validateLimit(long value, String name) {
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if (value < 0L || (value > 0L && value < MIN_ENABLED_LIMIT)) {
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throw new IllegalArgumentException(name + " 必须为 0 或至少 " + MIN_ENABLED_LIMIT);
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}
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}
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public void truncateNormalRow(Map<String, Object> row) {
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if (row == null || normalMaxBytes == 0L) return;
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for (String field : normalFields) {
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Object value = row.get(field);
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if (!(value instanceof String)) continue;
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Utf8TextTruncator.Result result = Utf8TextTruncator.truncate((String) value, normalMaxBytes);
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if (result.isTruncated()) {
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row.put(field, result.getValue());
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normalFieldsTruncated.increment();
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}
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}
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}
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public void truncateNonNormal(SyslogNonNormalMessage message) {
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if (message == null || nonNormalMaxBytes == 0L) return;
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message.setSyslogMessage(truncateNonNormalValue(message.getSyslogMessage()));
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message.setHeaderMessage(truncateNonNormalValue(message.getHeaderMessage()));
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message.setReasonDetail(truncateNonNormalValue(message.getReasonDetail()));
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}
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private String truncateNonNormalValue(String value) {
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Utf8TextTruncator.Result result = Utf8TextTruncator.truncate(value, nonNormalMaxBytes);
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if (result.isTruncated()) nonNormalFieldsTruncated.increment();
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return result.getValue();
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}
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public long getNormalFieldsTruncated() { return normalFieldsTruncated.sum(); }
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public long getNonNormalFieldsTruncated() { return nonNormalFieldsTruncated.sum(); }
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/** 测试和非 Spring 兼容入口。 */
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static DmLargeTextLimiter unlimited() {
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DmLargeTextLimiter limiter = new DmLargeTextLimiter();
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limiter.normalMaxBytes = 0L;
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limiter.nonNormalMaxBytes = 0L;
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limiter.validate();
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return limiter;
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}
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}
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+3
-3
@@ -174,8 +174,8 @@ public class DmStandardizedBatchExecutor {
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lateAlarmBucketWriter.record(rows);
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}
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// DIRECT/SHADOW 模式在当前事务内按设备、规则聚合写统计;LEGACY 模式会直接返回。
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// 任一统计 SQL 失败都会回滚本事务的事实行,禁止产生无法定位的统计缺口。
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// DIRECT 异步投影模式只在当前事实事务追加一条聚合 Outbox;独立 Kafka consumer
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// 再更新日统计。SHADOW/回退模式仍保留原同步 MERGE。
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timing.statsResult = directStatsProjectionWriter.writeStandardizedRows(rows);
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return null;
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});
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@@ -183,7 +183,7 @@ public class DmStandardizedBatchExecutor {
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transactionMetrics.recordSuccess(rows.size(), timing.factFlushMs, timing.commitMs, transactionMs);
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if (transactionLogEnabled && timing.statsResult != null && timing.statsResult.isDirect()) {
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log.info("DIRECT 达梦事务完成: factRows={}, deviceGroups={}, ruleGroups={}, aggregateMs={}, " +
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"factFlushMs={}, statsMergeMs={}, materializeMs={}, commitMs={}, transactionMs={}, retry={}",
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"factFlushMs={}, statsProjectionStageMs={}, materializeMs={}, commitMs={}, transactionMs={}, retry={}",
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rows.size(), timing.statsResult.getDeviceGroups(), timing.statsResult.getRuleGroups(),
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timing.statsResult.getAggregateMs(), timing.factFlushMs,
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timing.statsResult.getMergeMs(), timing.statsResult.getMaterializeMs(),
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+13
-1
@@ -60,6 +60,7 @@ public class DmStandardizedBatchWriter {
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private final SyslogNormalDataService normalDataService;
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private final DmStandardizedBatchExecutor batchExecutor;
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private final Executor writerExecutor;
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private final DmLargeTextLimiter largeTextLimiter;
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// 未配置时直接启用本次改造的批写路径;SINGLE 只作为现场故障回退开关保留。
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@Value("${dm.standardized-write.mode:BATCH}")
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@@ -89,12 +90,22 @@ public class DmStandardizedBatchWriter {
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private final AtomicInteger consecutiveSystemFailures = new AtomicInteger();
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private volatile long circuitOpenUntilMs;
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@org.springframework.beans.factory.annotation.Autowired
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public DmStandardizedBatchWriter(SyslogNormalDataService normalDataService,
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DmStandardizedBatchExecutor batchExecutor,
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@Qualifier("dmStandardizedWriterExecutor") Executor writerExecutor) {
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@Qualifier("dmStandardizedWriterExecutor") Executor writerExecutor,
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DmLargeTextLimiter largeTextLimiter) {
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this.normalDataService = normalDataService;
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this.batchExecutor = batchExecutor;
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this.writerExecutor = writerExecutor;
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this.largeTextLimiter = largeTextLimiter;
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}
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/** 保留已有单元测试和离线工具入口,默认不改变历史存储内容。 */
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public DmStandardizedBatchWriter(SyslogNormalDataService normalDataService,
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DmStandardizedBatchExecutor batchExecutor,
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Executor writerExecutor) {
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this(normalDataService, batchExecutor, writerExecutor, DmLargeTextLimiter.unlimited());
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}
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/**
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@@ -148,6 +159,7 @@ public class DmStandardizedBatchWriter {
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List<WriteRequest<T>> prepared = new ArrayList<>(requests.size());
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for (WriteRequest<T> request : requests) {
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try {
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largeTextLimiter.truncateNormalRow(request.getData());
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normalDataService.prepareForInsert(request.getData());
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prepared.add(request);
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} catch (RuntimeException invalidRow) {
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+15
-1
@@ -29,6 +29,7 @@ public class IngressStatsProjectionWriter {
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private final PlatformTransactionManager transactionManager;
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private final StatsWriteModeProvider modeProvider;
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private final StatsMaterializationPublisher materializationPublisher;
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private final StatsProjectionOutboxWriter projectionOutboxWriter;
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@Value("${stats.ingress-metadata.enabled:false}")
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private boolean enabled;
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@@ -50,11 +51,13 @@ public class IngressStatsProjectionWriter {
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public IngressStatsProjectionWriter(JdbcTemplate jdbc,
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PlatformTransactionManager transactionManager,
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StatsWriteModeProvider modeProvider,
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StatsMaterializationPublisher materializationPublisher) {
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StatsMaterializationPublisher materializationPublisher,
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StatsProjectionOutboxWriter projectionOutboxWriter) {
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this.jdbc = jdbc;
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this.transactionManager = transactionManager;
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this.modeProvider = modeProvider;
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this.materializationPublisher = materializationPublisher;
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this.projectionOutboxWriter = projectionOutboxWriter;
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}
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public int writeBatch(List<IngressStatsEvent> events) {
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@@ -92,6 +95,8 @@ public class IngressStatsProjectionWriter {
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? "device_daily_stats+" + shadowDeviceTable : "device_daily_stats");
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status.put("business_materialization_mode", asynchronousMaterialization()
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? "KAFKA_DIRTY_KEY" : "SYNCHRONOUS");
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status.put("daily_projection_write_mode", asynchronousProjection()
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? "DURABLE_OUTBOX" : "SYNCHRONOUS_MERGE");
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status.put("successful_batches", successfulBatches.get());
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status.put("received_events", receivedEvents.get());
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status.put("updated_groups", updatedGroups.get());
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@@ -109,6 +114,10 @@ public class IngressStatsProjectionWriter {
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TransactionTemplate transaction = new TransactionTemplate(transactionManager);
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transaction.setTimeout(Math.max(1, transactionTimeoutSeconds));
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Integer updated = transaction.execute(status -> {
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if (asynchronousProjection()) {
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projectionOutboxWriter.append(StatsProjectionOutboxEvent.fromIngress(aggregation));
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return aggregation.devices.size() + aggregation.collects.size();
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}
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int groups = 0;
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boolean asyncMaterialization = asynchronousMaterialization();
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List<StatsMaterializationCommand> commands = asyncMaterialization
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@@ -237,6 +246,11 @@ public class IngressStatsProjectionWriter {
|
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&& materializationPublisher.isEnabled();
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}
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private boolean asynchronousProjection() {
|
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return modeProvider.getMode() == StatsWriteModeProvider.Mode.DIRECT
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&& projectionOutboxWriter != null && projectionOutboxWriter.isEnabled();
|
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}
|
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|
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private static String safeTable(String table) {
|
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if (table == null || !table.matches("[A-Za-z][A-Za-z0-9_]*")) {
|
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throw new IllegalStateException("非法入口设备统计表名: " + table);
|
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|
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+386
@@ -0,0 +1,386 @@
|
||||
package com.common.service;
|
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|
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import com.fasterxml.jackson.databind.ObjectMapper;
|
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import lombok.extern.slf4j.Slf4j;
|
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import org.apache.kafka.clients.consumer.ConsumerRecord;
|
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import org.springframework.beans.factory.annotation.Value;
|
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import org.springframework.jdbc.core.JdbcTemplate;
|
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import org.springframework.kafka.annotation.KafkaListener;
|
||||
import org.springframework.kafka.support.Acknowledgment;
|
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import org.springframework.stereotype.Component;
|
||||
import org.springframework.transaction.PlatformTransactionManager;
|
||||
import org.springframework.transaction.support.TransactionTemplate;
|
||||
|
||||
import java.sql.Date;
|
||||
import java.time.LocalDate;
|
||||
import java.time.LocalDateTime;
|
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import java.util.ArrayList;
|
||||
import java.util.Arrays;
|
||||
import java.util.Collection;
|
||||
import java.util.Collections;
|
||||
import java.util.Comparator;
|
||||
import java.util.HashSet;
|
||||
import java.util.LinkedHashMap;
|
||||
import java.util.LinkedHashSet;
|
||||
import java.util.List;
|
||||
import java.util.Map;
|
||||
import java.util.Set;
|
||||
import java.util.TreeMap;
|
||||
import java.util.concurrent.atomic.AtomicLong;
|
||||
|
||||
/** Applies durable projection deltas outside the fact transaction. */
|
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@Slf4j
|
||||
@Component
|
||||
public class StatsProjectionDeltaConsumer {
|
||||
private static final String DEVICE_MERGE =
|
||||
"MERGE INTO %s t USING (SELECT ? stat_date,? device_id,? parse_delta," +
|
||||
"? non_log_delta,? receive_time FROM DUAL) s " +
|
||||
"ON (t.stat_date=s.stat_date AND t.device_id=s.device_id) " +
|
||||
"WHEN MATCHED THEN UPDATE SET t.parse_count=t.parse_count+s.parse_delta," +
|
||||
"t.non_log_count=t.non_log_count+s.non_log_delta," +
|
||||
"t.last_receive_time=CASE WHEN s.receive_time IS NULL THEN t.last_receive_time " +
|
||||
"WHEN t.last_receive_time IS NULL OR t.last_receive_time<s.receive_time " +
|
||||
"THEN s.receive_time ELSE t.last_receive_time END," +
|
||||
"t.projection_seq=t.projection_seq+1,t.updated_at=SYSDATE " +
|
||||
"WHEN NOT MATCHED THEN INSERT (stat_date,device_id,parse_count,non_log_count," +
|
||||
"last_receive_time,projection_seq,updated_at) VALUES " +
|
||||
"(s.stat_date,s.device_id,s.parse_delta,s.non_log_delta,s.receive_time,1,SYSDATE)";
|
||||
|
||||
private static final String RULE_MERGE =
|
||||
"MERGE INTO %s t USING (SELECT ? stat_date,? normalize_rule_id,? max_log_time FROM DUAL) s " +
|
||||
"ON (t.stat_date=s.stat_date AND t.normalize_rule_id=s.normalize_rule_id) " +
|
||||
"WHEN MATCHED THEN UPDATE SET t.max_log_time=CASE " +
|
||||
"WHEN t.max_log_time IS NULL OR t.max_log_time<s.max_log_time THEN s.max_log_time " +
|
||||
"ELSE t.max_log_time END,t.projection_seq=t.projection_seq+1,t.updated_at=SYSDATE " +
|
||||
"WHEN NOT MATCHED THEN INSERT (stat_date,normalize_rule_id,max_log_time,projection_seq,updated_at) " +
|
||||
"VALUES (s.stat_date,s.normalize_rule_id,s.max_log_time,1,SYSDATE)";
|
||||
|
||||
private static final String COLLECT_MERGE =
|
||||
"MERGE INTO device_collect_stats t USING (SELECT ? device_collect_id," +
|
||||
"? first_success_time,? last_success_time FROM DUAL) s " +
|
||||
"ON (t.device_collect_id=s.device_collect_id) " +
|
||||
"WHEN MATCHED THEN UPDATE SET t.first_success_time=CASE " +
|
||||
"WHEN s.first_success_time IS NULL THEN t.first_success_time " +
|
||||
"WHEN t.first_success_time IS NULL OR t.first_success_time>s.first_success_time " +
|
||||
"THEN s.first_success_time ELSE t.first_success_time END," +
|
||||
"t.last_success_time=CASE WHEN s.last_success_time IS NULL THEN t.last_success_time " +
|
||||
"WHEN t.last_success_time IS NULL OR t.last_success_time<s.last_success_time " +
|
||||
"THEN s.last_success_time ELSE t.last_success_time END," +
|
||||
"t.projection_seq=t.projection_seq+1,t.updated_at=SYSDATE " +
|
||||
"WHEN NOT MATCHED THEN INSERT (device_collect_id,first_success_time,last_success_time," +
|
||||
"last_fail_time,projection_seq,updated_at) VALUES " +
|
||||
"(s.device_collect_id,s.first_success_time,s.last_success_time,NULL,1,SYSDATE)";
|
||||
|
||||
private final JdbcTemplate jdbc;
|
||||
private final PlatformTransactionManager transactionManager;
|
||||
private final ObjectMapper objectMapper;
|
||||
private final StatsMaterializationPublisher materializationPublisher;
|
||||
|
||||
@Value("${stats.projection-async.enabled:true}") private boolean enabled;
|
||||
@Value("${stats.projection-async.applied-table:stats_projection_applied_event}") private String appliedTable;
|
||||
@Value("${stats.projection-async.outbox-table:stats_projection_outbox}") private String outboxTable;
|
||||
@Value("${stats.direct.device-table:device_daily_stats}") private String deviceTable;
|
||||
@Value("${stats.direct.rule-table:normalize_rule_daily_stats}") private String ruleTable;
|
||||
@Value("${stats.incremental.transaction-timeout-seconds:45}") private int transactionTimeoutSeconds;
|
||||
@Value("${stats.projection-async.max-concurrency-retries:3}") private int maxConcurrencyRetries;
|
||||
@Value("${stats.projection-async.concurrency-retry-backoff-ms:50}") private long retryBackoffMs;
|
||||
|
||||
private final AtomicLong consumed = new AtomicLong();
|
||||
private final AtomicLong appliedEvents = new AtomicLong();
|
||||
private final AtomicLong duplicates = new AtomicLong();
|
||||
private final AtomicLong deviceGroups = new AtomicLong();
|
||||
private final AtomicLong ruleGroups = new AtomicLong();
|
||||
private final AtomicLong collectGroups = new AtomicLong();
|
||||
private final AtomicLong successfulBatches = new AtomicLong();
|
||||
private final AtomicLong failures = new AtomicLong();
|
||||
private final AtomicLong retries = new AtomicLong();
|
||||
private volatile LocalDateTime lastSuccessTime;
|
||||
private volatile LocalDateTime lastFailureTime;
|
||||
|
||||
public StatsProjectionDeltaConsumer(JdbcTemplate jdbc,
|
||||
PlatformTransactionManager transactionManager,
|
||||
ObjectMapper objectMapper,
|
||||
StatsMaterializationPublisher materializationPublisher) {
|
||||
this.jdbc = jdbc;
|
||||
this.transactionManager = transactionManager;
|
||||
this.objectMapper = objectMapper.copy();
|
||||
this.objectMapper.deactivateDefaultTyping();
|
||||
this.materializationPublisher = materializationPublisher;
|
||||
}
|
||||
|
||||
@KafkaListener(
|
||||
id = "syslog-stats-projection",
|
||||
groupId = "${stats.projection-async.group-id:${spring.kafka.consumer.group-id}-stats-projection}",
|
||||
topics = "${stats.projection-async.topic:${spring.kafka.consumer.topic}.STATS.PROJECTION}",
|
||||
autoStartup = "${stats.projection-async.enabled:true}",
|
||||
containerFactory = "statsProjectionKafkaListenerContainerFactory"
|
||||
)
|
||||
public void consume(List<ConsumerRecord<String, String>> records, Acknowledgment acknowledgment) {
|
||||
if (records == null || records.isEmpty()) {
|
||||
acknowledgment.acknowledge();
|
||||
return;
|
||||
}
|
||||
consumed.addAndGet(records.size());
|
||||
List<StatsProjectionOutboxEvent> events = parse(records);
|
||||
long started = System.nanoTime();
|
||||
try {
|
||||
ApplyResult result = applyWithRetry(events);
|
||||
acknowledgment.acknowledge();
|
||||
appliedEvents.addAndGet(result.appliedEvents);
|
||||
duplicates.addAndGet(result.duplicates);
|
||||
deviceGroups.addAndGet(result.deviceGroups);
|
||||
ruleGroups.addAndGet(result.ruleGroups);
|
||||
collectGroups.addAndGet(result.collectGroups);
|
||||
successfulBatches.incrementAndGet();
|
||||
lastSuccessTime = LocalDateTime.now();
|
||||
log.info("统计投影批次完成: received={}, appliedEvents={}, duplicates={}, " +
|
||||
"deviceGroups={}, ruleGroups={}, collectGroups={}, durationMs={}",
|
||||
records.size(), result.appliedEvents, result.duplicates,
|
||||
result.deviceGroups, result.ruleGroups, result.collectGroups,
|
||||
(System.nanoTime() - started) / 1_000_000L);
|
||||
} catch (RuntimeException failure) {
|
||||
failures.incrementAndGet();
|
||||
lastFailureTime = LocalDateTime.now();
|
||||
throw failure;
|
||||
}
|
||||
}
|
||||
|
||||
private List<StatsProjectionOutboxEvent> parse(List<ConsumerRecord<String, String>> records) {
|
||||
Map<String, StatsProjectionOutboxEvent> unique = new LinkedHashMap<>();
|
||||
for (ConsumerRecord<String, String> record : records) {
|
||||
try {
|
||||
if (!StatsProjectionOutboxEvent.KAFKA_KEY.equals(record.key())) {
|
||||
throw new IllegalArgumentException("Unexpected stats projection Kafka key: " + record.key());
|
||||
}
|
||||
StatsProjectionOutboxEvent event = objectMapper.readValue(
|
||||
record.value(), StatsProjectionOutboxEvent.class);
|
||||
event.validate();
|
||||
unique.put(event.getEventId(), event);
|
||||
} catch (Exception invalid) {
|
||||
throw new IllegalStateException("Invalid internal stats projection event at " +
|
||||
record.topic() + "-" + record.partition() + "@" + record.offset(), invalid);
|
||||
}
|
||||
}
|
||||
return new ArrayList<>(unique.values());
|
||||
}
|
||||
|
||||
ApplyResult applyWithRetry(List<StatsProjectionOutboxEvent> events) {
|
||||
int attempt = 0;
|
||||
while (true) {
|
||||
try {
|
||||
return applyOnce(events);
|
||||
} catch (RuntimeException failure) {
|
||||
if (!DirectStatsProjectionWriter.isConcurrentFailure(failure)
|
||||
|| attempt >= Math.max(0, maxConcurrencyRetries)) {
|
||||
throw failure;
|
||||
}
|
||||
attempt++;
|
||||
retries.incrementAndGet();
|
||||
sleepBeforeRetry(attempt);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
private ApplyResult applyOnce(List<StatsProjectionOutboxEvent> events) {
|
||||
if (!enabled) throw new IllegalStateException("Stats projection consumer is disabled");
|
||||
TransactionTemplate transaction = new TransactionTemplate(transactionManager);
|
||||
transaction.setTimeout(Math.max(1, transactionTimeoutSeconds));
|
||||
ApplyResult result = transaction.execute(status -> {
|
||||
Set<String> existing = existingEventIds(events);
|
||||
List<StatsProjectionOutboxEvent> fresh = new ArrayList<>();
|
||||
for (StatsProjectionOutboxEvent event : events) {
|
||||
if (!existing.contains(event.getEventId())) fresh.add(event);
|
||||
}
|
||||
ProjectionAggregation aggregation = aggregate(fresh);
|
||||
if (!aggregation.devices.isEmpty()) {
|
||||
jdbc.batchUpdate(String.format(DEVICE_MERGE,
|
||||
StatsProjectionOutboxWriter.safeTable(deviceTable)), aggregation.deviceParams());
|
||||
}
|
||||
if (!aggregation.rules.isEmpty()) {
|
||||
jdbc.batchUpdate(String.format(RULE_MERGE,
|
||||
StatsProjectionOutboxWriter.safeTable(ruleTable)), aggregation.ruleParams());
|
||||
}
|
||||
if (!aggregation.collects.isEmpty()) {
|
||||
jdbc.batchUpdate(COLLECT_MERGE, aggregation.collectParams());
|
||||
}
|
||||
if (!fresh.isEmpty()) {
|
||||
List<Object[]> markers = new ArrayList<>(fresh.size());
|
||||
for (StatsProjectionOutboxEvent event : fresh) {
|
||||
markers.add(new Object[]{event.getEventId(), event.getSchema()});
|
||||
}
|
||||
jdbc.batchUpdate("INSERT INTO " + StatsProjectionOutboxWriter.safeTable(appliedTable) +
|
||||
" (event_id,event_schema,applied_at) VALUES (?,?,SYSDATE)", markers);
|
||||
}
|
||||
if (!events.isEmpty()) {
|
||||
List<Object[]> acknowledged = new ArrayList<>(events.size());
|
||||
for (StatsProjectionOutboxEvent event : events) {
|
||||
acknowledged.add(new Object[]{event.getEventId()});
|
||||
}
|
||||
jdbc.batchUpdate("UPDATE " + StatsProjectionOutboxWriter.safeTable(outboxTable) +
|
||||
" SET status='APPLIED',applied_at=SYSDATE,next_attempt_at=NULL," +
|
||||
"updated_at=SYSDATE WHERE event_id=?", acknowledged);
|
||||
}
|
||||
Collection<StatsMaterializationCommand> dirty = aggregation.materializationCommands();
|
||||
if (!dirty.isEmpty()) materializationPublisher.enqueueAfterCommit(dirty);
|
||||
return new ApplyResult(fresh.size(), events.size() - fresh.size(),
|
||||
aggregation.devices.size(), aggregation.rules.size(), aggregation.collects.size());
|
||||
});
|
||||
return result == null ? new ApplyResult(0, events.size(), 0, 0, 0) : result;
|
||||
}
|
||||
|
||||
private Set<String> existingEventIds(List<StatsProjectionOutboxEvent> events) {
|
||||
if (events.isEmpty()) return Collections.emptySet();
|
||||
Set<String> result = new HashSet<>();
|
||||
int chunkSize = 900;
|
||||
for (int start = 0; start < events.size(); start += chunkSize) {
|
||||
int end = Math.min(events.size(), start + chunkSize);
|
||||
StringBuilder placeholders = new StringBuilder();
|
||||
Object[] ids = new Object[end - start];
|
||||
for (int i = start; i < end; i++) {
|
||||
if (placeholders.length() > 0) placeholders.append(',');
|
||||
placeholders.append('?');
|
||||
ids[i - start] = events.get(i).getEventId();
|
||||
}
|
||||
result.addAll(jdbc.queryForList("SELECT event_id FROM " +
|
||||
StatsProjectionOutboxWriter.safeTable(appliedTable) + " WHERE event_id IN (" +
|
||||
placeholders + ")", String.class, ids));
|
||||
}
|
||||
return result;
|
||||
}
|
||||
|
||||
static ProjectionAggregation aggregate(List<StatsProjectionOutboxEvent> events) {
|
||||
ProjectionAggregation result = new ProjectionAggregation();
|
||||
for (StatsProjectionOutboxEvent event : events) {
|
||||
event.validate();
|
||||
for (StatsProjectionOutboxEvent.DeviceDelta delta : event.getDevices()) {
|
||||
DeviceKey key = new DeviceKey(delta.date(), delta.getDeviceId());
|
||||
DeviceAggregate value = result.devices.computeIfAbsent(key,
|
||||
ignored -> new DeviceAggregate());
|
||||
value.parseDelta += delta.getParseDelta();
|
||||
value.nonLogDelta += delta.getNonLogDelta();
|
||||
LocalDateTime receiveTime = delta.receiveTime();
|
||||
if (receiveTime != null && (value.lastReceiveTime == null
|
||||
|| receiveTime.isAfter(value.lastReceiveTime))) {
|
||||
value.lastReceiveTime = receiveTime;
|
||||
}
|
||||
}
|
||||
for (StatsProjectionOutboxEvent.RuleDelta delta : event.getRules()) {
|
||||
RuleKey key = new RuleKey(delta.date(), delta.getNormalizeRuleId());
|
||||
LocalDateTime value = delta.time();
|
||||
LocalDateTime current = result.rules.get(key);
|
||||
if (current == null || value.isAfter(current)) result.rules.put(key, value);
|
||||
}
|
||||
for (StatsProjectionOutboxEvent.CollectDelta delta : event.getCollects()) {
|
||||
CollectAggregate value = result.collects.computeIfAbsent(delta.getDeviceCollectId(),
|
||||
ignored -> new CollectAggregate());
|
||||
value.include(delta.firstTime());
|
||||
value.include(delta.lastTime());
|
||||
}
|
||||
}
|
||||
return result;
|
||||
}
|
||||
|
||||
private void sleepBeforeRetry(int attempt) {
|
||||
try {
|
||||
Thread.sleep(Math.max(0L, retryBackoffMs) * attempt);
|
||||
} catch (InterruptedException interrupted) {
|
||||
Thread.currentThread().interrupt();
|
||||
throw new IllegalStateException("Stats projection retry interrupted", interrupted);
|
||||
}
|
||||
}
|
||||
|
||||
public Map<String, Object> status() {
|
||||
Map<String, Object> result = new LinkedHashMap<>();
|
||||
result.put("enabled", enabled);
|
||||
result.put("consumed_total", consumed.get());
|
||||
result.put("applied_events_total", appliedEvents.get());
|
||||
result.put("duplicate_events_total", duplicates.get());
|
||||
result.put("device_groups_total", deviceGroups.get());
|
||||
result.put("rule_groups_total", ruleGroups.get());
|
||||
result.put("collect_groups_total", collectGroups.get());
|
||||
result.put("successful_batches", successfulBatches.get());
|
||||
result.put("failures_total", failures.get());
|
||||
result.put("concurrency_retries_total", retries.get());
|
||||
result.put("last_success_time", lastSuccessTime);
|
||||
result.put("last_failure_time", lastFailureTime);
|
||||
return result;
|
||||
}
|
||||
|
||||
static final class ProjectionAggregation {
|
||||
final Map<DeviceKey, DeviceAggregate> devices = new TreeMap<>();
|
||||
final Map<RuleKey, LocalDateTime> rules = new TreeMap<>();
|
||||
final Map<Long, CollectAggregate> collects = new TreeMap<>();
|
||||
|
||||
List<Object[]> deviceParams() {
|
||||
List<Object[]> result = new ArrayList<>(devices.size());
|
||||
for (Map.Entry<DeviceKey, DeviceAggregate> entry : devices.entrySet()) {
|
||||
DeviceAggregate value = entry.getValue();
|
||||
result.add(new Object[]{Date.valueOf(entry.getKey().date), entry.getKey().id,
|
||||
value.parseDelta, value.nonLogDelta, value.lastReceiveTime});
|
||||
}
|
||||
return result;
|
||||
}
|
||||
|
||||
List<Object[]> ruleParams() {
|
||||
List<Object[]> result = new ArrayList<>(rules.size());
|
||||
for (Map.Entry<RuleKey, LocalDateTime> entry : rules.entrySet()) {
|
||||
result.add(new Object[]{Date.valueOf(entry.getKey().date), entry.getKey().id,
|
||||
entry.getValue()});
|
||||
}
|
||||
return result;
|
||||
}
|
||||
|
||||
List<Object[]> collectParams() {
|
||||
List<Object[]> result = new ArrayList<>(collects.size());
|
||||
for (Map.Entry<Long, CollectAggregate> entry : collects.entrySet()) {
|
||||
result.add(new Object[]{entry.getKey(), entry.getValue().min, entry.getValue().max});
|
||||
}
|
||||
return result;
|
||||
}
|
||||
|
||||
Collection<StatsMaterializationCommand> materializationCommands() {
|
||||
Set<StatsMaterializationCommand> result = new LinkedHashSet<>();
|
||||
for (DeviceKey key : devices.keySet()) result.add(StatsMaterializationCommand.device(key.date, key.id));
|
||||
for (RuleKey key : rules.keySet()) result.add(StatsMaterializationCommand.rule(key.date, key.id));
|
||||
for (Long id : collects.keySet()) result.add(StatsMaterializationCommand.collect(id));
|
||||
return result;
|
||||
}
|
||||
}
|
||||
|
||||
static class DimensionKey implements Comparable<DimensionKey> {
|
||||
final LocalDate date;
|
||||
final long id;
|
||||
DimensionKey(LocalDate date, long id) { this.date = date; this.id = id; }
|
||||
@Override public int compareTo(DimensionKey other) {
|
||||
int dateOrder = date.compareTo(other.date);
|
||||
return dateOrder != 0 ? dateOrder : Long.compare(id, other.id);
|
||||
}
|
||||
@Override public boolean equals(Object other) {
|
||||
if (this == other) return true;
|
||||
if (!(other instanceof DimensionKey)) return false;
|
||||
DimensionKey key = (DimensionKey) other;
|
||||
return id == key.id && date.equals(key.date);
|
||||
}
|
||||
@Override public int hashCode() { return 31 * date.hashCode() + Long.hashCode(id); }
|
||||
}
|
||||
static final class DeviceKey extends DimensionKey { DeviceKey(LocalDate date, long id) { super(date, id); } }
|
||||
static final class RuleKey extends DimensionKey { RuleKey(LocalDate date, long id) { super(date, id); } }
|
||||
static final class DeviceAggregate { long parseDelta; long nonLogDelta; LocalDateTime lastReceiveTime; }
|
||||
static final class CollectAggregate {
|
||||
LocalDateTime min; LocalDateTime max;
|
||||
void include(LocalDateTime time) {
|
||||
if (time == null) return;
|
||||
if (min == null || time.isBefore(min)) min = time;
|
||||
if (max == null || time.isAfter(max)) max = time;
|
||||
}
|
||||
}
|
||||
|
||||
static final class ApplyResult {
|
||||
final int appliedEvents; final int duplicates;
|
||||
final int deviceGroups; final int ruleGroups; final int collectGroups;
|
||||
ApplyResult(int appliedEvents, int duplicates, int deviceGroups, int ruleGroups, int collectGroups) {
|
||||
this.appliedEvents = appliedEvents; this.duplicates = duplicates;
|
||||
this.deviceGroups = deviceGroups; this.ruleGroups = ruleGroups; this.collectGroups = collectGroups;
|
||||
}
|
||||
}
|
||||
}
|
||||
+221
@@ -0,0 +1,221 @@
|
||||
package com.common.service;
|
||||
|
||||
import com.fasterxml.jackson.annotation.JsonIgnoreProperties;
|
||||
|
||||
import java.time.LocalDate;
|
||||
import java.time.LocalDateTime;
|
||||
import java.util.ArrayList;
|
||||
import java.util.List;
|
||||
import java.util.Map;
|
||||
import java.util.UUID;
|
||||
|
||||
/**
|
||||
* A durable, batch-aggregated statistics delta written beside the fact rows.
|
||||
*
|
||||
* <p>The event is additive/max-min only, so events from different application nodes may be
|
||||
* published in a different order without changing the final projection. Kafka duplicates are
|
||||
* eliminated by {@code eventId} in the projection consumer transaction.</p>
|
||||
*/
|
||||
@JsonIgnoreProperties(ignoreUnknown = true)
|
||||
public class StatsProjectionOutboxEvent {
|
||||
public static final String SCHEMA = "SYSLOG_STATS_PROJECTION_V1";
|
||||
public static final String KAFKA_KEY = "SYSLOG_STATS_PROJECTION";
|
||||
|
||||
private String schema = SCHEMA;
|
||||
private String eventId = UUID.randomUUID().toString();
|
||||
private List<DeviceDelta> devices = new ArrayList<>();
|
||||
private List<RuleDelta> rules = new ArrayList<>();
|
||||
private List<CollectDelta> collects = new ArrayList<>();
|
||||
|
||||
public static StatsProjectionOutboxEvent fromAccumulator(DirectStatsAccumulator accumulator) {
|
||||
StatsProjectionOutboxEvent event = new StatsProjectionOutboxEvent();
|
||||
for (Map.Entry<DirectStatsAccumulator.DailyKey, DirectStatsAccumulator.DeviceDelta> entry
|
||||
: accumulator.getDevices().entrySet()) {
|
||||
DirectStatsAccumulator.DeviceDelta value = entry.getValue();
|
||||
if (value.getParseDelta() != 0L || value.getNonLogDelta() != 0L) {
|
||||
event.devices.add(DeviceDelta.counts(entry.getKey().getDate(),
|
||||
entry.getKey().getDimensionId(), value.getParseDelta(), value.getNonLogDelta()));
|
||||
}
|
||||
}
|
||||
for (Map.Entry<DirectStatsAccumulator.DailyKey, DirectStatsAccumulator.RuleDelta> entry
|
||||
: accumulator.getRules().entrySet()) {
|
||||
if (entry.getValue().getMaxLogTime() != null) {
|
||||
event.rules.add(RuleDelta.max(entry.getKey().getDate(),
|
||||
entry.getKey().getDimensionId(), entry.getValue().getMaxLogTime()));
|
||||
}
|
||||
}
|
||||
return event;
|
||||
}
|
||||
|
||||
static StatsProjectionOutboxEvent fromIngress(IngressStatsProjectionWriter.Aggregation aggregation) {
|
||||
StatsProjectionOutboxEvent event = new StatsProjectionOutboxEvent();
|
||||
for (Map.Entry<IngressStatsProjectionWriter.DeviceKey, LocalDateTime> entry
|
||||
: aggregation.devices.entrySet()) {
|
||||
event.devices.add(DeviceDelta.received(entry.getKey().date,
|
||||
entry.getKey().deviceId, entry.getValue()));
|
||||
}
|
||||
for (Map.Entry<Long, IngressStatsProjectionWriter.CollectTimes> entry
|
||||
: aggregation.collects.entrySet()) {
|
||||
event.collects.add(CollectDelta.range(entry.getKey(),
|
||||
entry.getValue().min, entry.getValue().max));
|
||||
}
|
||||
return event;
|
||||
}
|
||||
|
||||
public void validate() {
|
||||
if (!SCHEMA.equals(schema)) {
|
||||
throw new IllegalArgumentException("Unsupported stats projection schema: " + schema);
|
||||
}
|
||||
if (eventId == null || eventId.trim().isEmpty()) {
|
||||
throw new IllegalArgumentException("Stats projection event is missing eventId");
|
||||
}
|
||||
if (devices == null || rules == null || collects == null) {
|
||||
throw new IllegalArgumentException("Stats projection event contains null collections");
|
||||
}
|
||||
if (devices.isEmpty() && rules.isEmpty() && collects.isEmpty()) {
|
||||
throw new IllegalArgumentException("Stats projection event has no changes");
|
||||
}
|
||||
for (DeviceDelta delta : devices) delta.validate();
|
||||
for (RuleDelta delta : rules) delta.validate();
|
||||
for (CollectDelta delta : collects) delta.validate();
|
||||
}
|
||||
|
||||
public boolean isEmpty() {
|
||||
return devices.isEmpty() && rules.isEmpty() && collects.isEmpty();
|
||||
}
|
||||
|
||||
public String getSchema() { return schema; }
|
||||
public void setSchema(String schema) { this.schema = schema; }
|
||||
public String getEventId() { return eventId; }
|
||||
public void setEventId(String eventId) { this.eventId = eventId; }
|
||||
public List<DeviceDelta> getDevices() { return devices; }
|
||||
public void setDevices(List<DeviceDelta> devices) { this.devices = devices; }
|
||||
public List<RuleDelta> getRules() { return rules; }
|
||||
public void setRules(List<RuleDelta> rules) { this.rules = rules; }
|
||||
public List<CollectDelta> getCollects() { return collects; }
|
||||
public void setCollects(List<CollectDelta> collects) { this.collects = collects; }
|
||||
|
||||
@JsonIgnoreProperties(ignoreUnknown = true)
|
||||
public static class DeviceDelta {
|
||||
private String statDate;
|
||||
private long deviceId;
|
||||
private long parseDelta;
|
||||
private long nonLogDelta;
|
||||
private String lastReceiveTime;
|
||||
|
||||
public DeviceDelta() {}
|
||||
|
||||
static DeviceDelta counts(LocalDate date, long deviceId, long parseDelta, long nonLogDelta) {
|
||||
DeviceDelta result = new DeviceDelta();
|
||||
result.statDate = date.toString();
|
||||
result.deviceId = deviceId;
|
||||
result.parseDelta = parseDelta;
|
||||
result.nonLogDelta = nonLogDelta;
|
||||
return result;
|
||||
}
|
||||
|
||||
static DeviceDelta received(LocalDate date, long deviceId, LocalDateTime receiveTime) {
|
||||
DeviceDelta result = counts(date, deviceId, 0L, 0L);
|
||||
result.lastReceiveTime = receiveTime.toString();
|
||||
return result;
|
||||
}
|
||||
|
||||
void validate() {
|
||||
date();
|
||||
if (deviceId <= 0L) throw new IllegalArgumentException("Invalid device projection id");
|
||||
if (parseDelta == 0L && nonLogDelta == 0L && receiveTime() == null) {
|
||||
throw new IllegalArgumentException("Device projection delta is empty");
|
||||
}
|
||||
}
|
||||
|
||||
public LocalDate date() { return LocalDate.parse(statDate); }
|
||||
public LocalDateTime receiveTime() {
|
||||
return lastReceiveTime == null || lastReceiveTime.trim().isEmpty()
|
||||
? null : LocalDateTime.parse(lastReceiveTime);
|
||||
}
|
||||
public String getStatDate() { return statDate; }
|
||||
public void setStatDate(String statDate) { this.statDate = statDate; }
|
||||
public long getDeviceId() { return deviceId; }
|
||||
public void setDeviceId(long deviceId) { this.deviceId = deviceId; }
|
||||
public long getParseDelta() { return parseDelta; }
|
||||
public void setParseDelta(long parseDelta) { this.parseDelta = parseDelta; }
|
||||
public long getNonLogDelta() { return nonLogDelta; }
|
||||
public void setNonLogDelta(long nonLogDelta) { this.nonLogDelta = nonLogDelta; }
|
||||
public String getLastReceiveTime() { return lastReceiveTime; }
|
||||
public void setLastReceiveTime(String lastReceiveTime) { this.lastReceiveTime = lastReceiveTime; }
|
||||
}
|
||||
|
||||
@JsonIgnoreProperties(ignoreUnknown = true)
|
||||
public static class RuleDelta {
|
||||
private String statDate;
|
||||
private long normalizeRuleId;
|
||||
private String maxLogTime;
|
||||
|
||||
public RuleDelta() {}
|
||||
|
||||
static RuleDelta max(LocalDate date, long ruleId, LocalDateTime maxLogTime) {
|
||||
RuleDelta result = new RuleDelta();
|
||||
result.statDate = date.toString();
|
||||
result.normalizeRuleId = ruleId;
|
||||
result.maxLogTime = maxLogTime.toString();
|
||||
return result;
|
||||
}
|
||||
|
||||
void validate() {
|
||||
date();
|
||||
if (normalizeRuleId <= 0L || time() == null) {
|
||||
throw new IllegalArgumentException("Invalid rule projection delta");
|
||||
}
|
||||
}
|
||||
|
||||
public LocalDate date() { return LocalDate.parse(statDate); }
|
||||
public LocalDateTime time() {
|
||||
return maxLogTime == null || maxLogTime.trim().isEmpty()
|
||||
? null : LocalDateTime.parse(maxLogTime);
|
||||
}
|
||||
public String getStatDate() { return statDate; }
|
||||
public void setStatDate(String statDate) { this.statDate = statDate; }
|
||||
public long getNormalizeRuleId() { return normalizeRuleId; }
|
||||
public void setNormalizeRuleId(long normalizeRuleId) { this.normalizeRuleId = normalizeRuleId; }
|
||||
public String getMaxLogTime() { return maxLogTime; }
|
||||
public void setMaxLogTime(String maxLogTime) { this.maxLogTime = maxLogTime; }
|
||||
}
|
||||
|
||||
@JsonIgnoreProperties(ignoreUnknown = true)
|
||||
public static class CollectDelta {
|
||||
private long deviceCollectId;
|
||||
private String firstSuccessTime;
|
||||
private String lastSuccessTime;
|
||||
|
||||
public CollectDelta() {}
|
||||
|
||||
static CollectDelta range(long collectId, LocalDateTime first, LocalDateTime last) {
|
||||
CollectDelta result = new CollectDelta();
|
||||
result.deviceCollectId = collectId;
|
||||
result.firstSuccessTime = first == null ? null : first.toString();
|
||||
result.lastSuccessTime = last == null ? null : last.toString();
|
||||
return result;
|
||||
}
|
||||
|
||||
void validate() {
|
||||
if (deviceCollectId <= 0L || (firstTime() == null && lastTime() == null)) {
|
||||
throw new IllegalArgumentException("Invalid collector projection delta");
|
||||
}
|
||||
}
|
||||
|
||||
public LocalDateTime firstTime() {
|
||||
return firstSuccessTime == null || firstSuccessTime.trim().isEmpty()
|
||||
? null : LocalDateTime.parse(firstSuccessTime);
|
||||
}
|
||||
public LocalDateTime lastTime() {
|
||||
return lastSuccessTime == null || lastSuccessTime.trim().isEmpty()
|
||||
? null : LocalDateTime.parse(lastSuccessTime);
|
||||
}
|
||||
public long getDeviceCollectId() { return deviceCollectId; }
|
||||
public void setDeviceCollectId(long deviceCollectId) { this.deviceCollectId = deviceCollectId; }
|
||||
public String getFirstSuccessTime() { return firstSuccessTime; }
|
||||
public void setFirstSuccessTime(String firstSuccessTime) { this.firstSuccessTime = firstSuccessTime; }
|
||||
public String getLastSuccessTime() { return lastSuccessTime; }
|
||||
public void setLastSuccessTime(String lastSuccessTime) { this.lastSuccessTime = lastSuccessTime; }
|
||||
}
|
||||
}
|
||||
+151
@@ -0,0 +1,151 @@
|
||||
package com.common.service;
|
||||
|
||||
import lombok.extern.slf4j.Slf4j;
|
||||
import org.springframework.beans.factory.annotation.Value;
|
||||
import org.springframework.jdbc.core.JdbcTemplate;
|
||||
import org.springframework.kafka.core.KafkaTemplate;
|
||||
import org.springframework.kafka.support.SendResult;
|
||||
import org.springframework.scheduling.annotation.Scheduled;
|
||||
import org.springframework.stereotype.Component;
|
||||
import org.springframework.util.concurrent.ListenableFuture;
|
||||
|
||||
import java.sql.Timestamp;
|
||||
import java.util.ArrayList;
|
||||
import java.util.LinkedHashMap;
|
||||
import java.util.List;
|
||||
import java.util.Map;
|
||||
import java.util.concurrent.TimeUnit;
|
||||
import java.util.concurrent.atomic.AtomicBoolean;
|
||||
import java.util.concurrent.atomic.AtomicLong;
|
||||
|
||||
/**
|
||||
* Relays durable outbox events to the dedicated projection topic.
|
||||
*
|
||||
* <p>Multiple application nodes may relay the same row during a race. The consumer's applied-event
|
||||
* table makes that harmless, so the relay never needs a distributed lease that could stall the
|
||||
* fact path.</p>
|
||||
*/
|
||||
@Slf4j
|
||||
@Component
|
||||
public class StatsProjectionOutboxRelay {
|
||||
private final JdbcTemplate jdbc;
|
||||
private final KafkaTemplate<String, String> kafkaTemplate;
|
||||
private final AtomicBoolean running = new AtomicBoolean();
|
||||
private final AtomicLong published = new AtomicLong();
|
||||
private final AtomicLong failures = new AtomicLong();
|
||||
private final AtomicLong cleaned = new AtomicLong();
|
||||
private volatile long lastSuccessAt;
|
||||
private volatile long lastFailureAt;
|
||||
|
||||
@Value("${stats.projection-async.enabled:true}") private boolean enabled;
|
||||
@Value("${stats.projection-async.outbox-table:stats_projection_outbox}") private String outboxTable;
|
||||
@Value("${stats.projection-async.applied-table:stats_projection_applied_event}") private String appliedTable;
|
||||
@Value("${stats.projection-async.topic:${spring.kafka.consumer.topic}.STATS.PROJECTION}") private String topic;
|
||||
@Value("${stats.projection-async.relay-batch-size:100}") private int batchSize;
|
||||
@Value("${stats.projection-async.publish-timeout-ms:10000}") private long publishTimeoutMs;
|
||||
@Value("${stats.projection-async.retry-backoff-ms:1000}") private long retryBackoffMs;
|
||||
@Value("${stats.projection-async.redelivery-interval-ms:60000}") private long redeliveryIntervalMs;
|
||||
@Value("${stats.projection-async.retention-days:14}") private int retentionDays;
|
||||
|
||||
public StatsProjectionOutboxRelay(JdbcTemplate jdbc, KafkaTemplate<String, String> kafkaTemplate) {
|
||||
this.jdbc = jdbc;
|
||||
this.kafkaTemplate = kafkaTemplate;
|
||||
}
|
||||
|
||||
@Scheduled(fixedDelayString = "${stats.projection-async.relay-interval-ms:200}")
|
||||
public void relay() {
|
||||
if (!enabled || !running.compareAndSet(false, true)) return;
|
||||
try {
|
||||
for (OutboxRow row : loadDueRows()) {
|
||||
publish(row);
|
||||
}
|
||||
} catch (RuntimeException failure) {
|
||||
failures.incrementAndGet();
|
||||
lastFailureAt = System.currentTimeMillis();
|
||||
log.error("统计投影 Outbox 扫描失败,下轮自动重试", failure);
|
||||
} finally {
|
||||
running.set(false);
|
||||
}
|
||||
}
|
||||
|
||||
private List<OutboxRow> loadDueRows() {
|
||||
String table = StatsProjectionOutboxWriter.safeTable(outboxTable);
|
||||
String sql = "SELECT event_id,payload FROM (SELECT event_id,payload FROM " + table +
|
||||
" WHERE status IN ('PENDING','FAILED','PUBLISHED') AND (next_attempt_at IS NULL " +
|
||||
"OR next_attempt_at<=SYSDATE) ORDER BY created_at,event_id) WHERE ROWNUM<=?";
|
||||
return jdbc.query(sql, ps -> ps.setInt(1, Math.max(1, batchSize)),
|
||||
(rs, rowNum) -> new OutboxRow(rs.getString(1), rs.getString(2)));
|
||||
}
|
||||
|
||||
private void publish(OutboxRow row) {
|
||||
try {
|
||||
ListenableFuture<SendResult<String, String>> future = kafkaTemplate.send(
|
||||
topic, StatsProjectionOutboxEvent.KAFKA_KEY, row.payload);
|
||||
future.get(Math.max(1L, publishTimeoutMs), TimeUnit.MILLISECONDS);
|
||||
jdbc.update("UPDATE " + StatsProjectionOutboxWriter.safeTable(outboxTable) +
|
||||
" SET status='PUBLISHED',published_at=SYSDATE,next_attempt_at=?,last_error=NULL," +
|
||||
"updated_at=SYSDATE WHERE event_id=? AND status<>'APPLIED'",
|
||||
new Timestamp(System.currentTimeMillis() + Math.max(1000L, redeliveryIntervalMs)),
|
||||
row.eventId);
|
||||
published.incrementAndGet();
|
||||
lastSuccessAt = System.currentTimeMillis();
|
||||
} catch (InterruptedException interrupted) {
|
||||
Thread.currentThread().interrupt();
|
||||
markFailure(row, interrupted);
|
||||
} catch (Exception failure) {
|
||||
markFailure(row, failure);
|
||||
}
|
||||
}
|
||||
|
||||
private void markFailure(OutboxRow row, Exception failure) {
|
||||
failures.incrementAndGet();
|
||||
lastFailureAt = System.currentTimeMillis();
|
||||
String message = String.valueOf(failure.getMessage());
|
||||
if (message.length() > 1800) message = message.substring(0, 1800);
|
||||
try {
|
||||
jdbc.update("UPDATE " + StatsProjectionOutboxWriter.safeTable(outboxTable) +
|
||||
" SET status='FAILED',attempt_count=attempt_count+1,next_attempt_at=?," +
|
||||
"last_error=?,updated_at=SYSDATE WHERE event_id=? AND status<>'APPLIED'",
|
||||
new Timestamp(System.currentTimeMillis() + Math.max(0L, retryBackoffMs)),
|
||||
message, row.eventId);
|
||||
} catch (RuntimeException markFailure) {
|
||||
failure.addSuppressed(markFailure);
|
||||
}
|
||||
log.error("统计投影 Outbox 发布失败,将自动重试: eventId={}", row.eventId, failure);
|
||||
}
|
||||
|
||||
@Scheduled(initialDelayString = "${stats.projection-async.cleanup-initial-delay-ms:3600000}",
|
||||
fixedDelayString = "${stats.projection-async.cleanup-interval-ms:3600000}")
|
||||
public void cleanup() {
|
||||
if (!enabled) return;
|
||||
long keepMillis = TimeUnit.DAYS.toMillis(Math.max(1, retentionDays));
|
||||
Timestamp cutoff = new Timestamp(System.currentTimeMillis() - keepMillis);
|
||||
int removed = jdbc.update("DELETE FROM " + StatsProjectionOutboxWriter.safeTable(outboxTable) +
|
||||
" WHERE status='APPLIED' AND applied_at<?", cutoff);
|
||||
removed += jdbc.update("DELETE FROM " + StatsProjectionOutboxWriter.safeTable(appliedTable) +
|
||||
" WHERE applied_at<?", cutoff);
|
||||
cleaned.addAndGet(removed);
|
||||
}
|
||||
|
||||
public Map<String, Object> status() {
|
||||
Map<String, Object> result = new LinkedHashMap<>();
|
||||
result.put("enabled", enabled);
|
||||
result.put("topic", topic);
|
||||
result.put("running", running.get());
|
||||
result.put("published_total", published.get());
|
||||
result.put("failures_total", failures.get());
|
||||
result.put("cleaned_rows_total", cleaned.get());
|
||||
result.put("last_success_epoch_ms", lastSuccessAt == 0L ? null : lastSuccessAt);
|
||||
result.put("last_failure_epoch_ms", lastFailureAt == 0L ? null : lastFailureAt);
|
||||
return result;
|
||||
}
|
||||
|
||||
private static final class OutboxRow {
|
||||
private final String eventId;
|
||||
private final String payload;
|
||||
private OutboxRow(String eventId, String payload) {
|
||||
this.eventId = eventId;
|
||||
this.payload = payload;
|
||||
}
|
||||
}
|
||||
}
|
||||
+70
@@ -0,0 +1,70 @@
|
||||
package com.common.service;
|
||||
|
||||
import com.fasterxml.jackson.core.JsonProcessingException;
|
||||
import com.fasterxml.jackson.databind.ObjectMapper;
|
||||
import org.springframework.beans.factory.annotation.Value;
|
||||
import org.springframework.jdbc.core.JdbcTemplate;
|
||||
import org.springframework.stereotype.Component;
|
||||
import org.springframework.transaction.support.TransactionSynchronizationManager;
|
||||
|
||||
import java.util.LinkedHashMap;
|
||||
import java.util.Map;
|
||||
import java.util.concurrent.atomic.AtomicLong;
|
||||
|
||||
/** Writes one aggregated outbox row in the same transaction as the corresponding fact batch. */
|
||||
@Component
|
||||
public class StatsProjectionOutboxWriter {
|
||||
private final JdbcTemplate jdbc;
|
||||
private final ObjectMapper objectMapper;
|
||||
private final AtomicLong events = new AtomicLong();
|
||||
private final AtomicLong failures = new AtomicLong();
|
||||
|
||||
@Value("${stats.projection-async.enabled:true}") private boolean enabled;
|
||||
@Value("${stats.projection-async.outbox-table:stats_projection_outbox}") private String outboxTable;
|
||||
|
||||
public StatsProjectionOutboxWriter(JdbcTemplate jdbc, ObjectMapper objectMapper) {
|
||||
this.jdbc = jdbc;
|
||||
this.objectMapper = objectMapper.copy();
|
||||
this.objectMapper.deactivateDefaultTyping();
|
||||
}
|
||||
|
||||
public boolean isEnabled() { return enabled; }
|
||||
|
||||
public int append(StatsProjectionOutboxEvent event) {
|
||||
if (!enabled || event == null || event.isEmpty()) return 0;
|
||||
if (!TransactionSynchronizationManager.isActualTransactionActive()) {
|
||||
throw new IllegalStateException("Stats projection outbox must be written inside a transaction");
|
||||
}
|
||||
event.validate();
|
||||
try {
|
||||
int inserted = jdbc.update("INSERT INTO " + safeTable(outboxTable) +
|
||||
" (event_id,event_schema,payload,status,attempt_count,next_attempt_at," +
|
||||
"created_at,updated_at) VALUES (?,?,?,'PENDING',0,SYSDATE,SYSDATE,SYSDATE)",
|
||||
event.getEventId(), event.getSchema(), objectMapper.writeValueAsString(event));
|
||||
events.incrementAndGet();
|
||||
return inserted;
|
||||
} catch (JsonProcessingException serializationFailure) {
|
||||
failures.incrementAndGet();
|
||||
throw new IllegalStateException("Failed to serialize stats projection outbox event", serializationFailure);
|
||||
} catch (RuntimeException databaseFailure) {
|
||||
failures.incrementAndGet();
|
||||
throw databaseFailure;
|
||||
}
|
||||
}
|
||||
|
||||
public Map<String, Object> status() {
|
||||
Map<String, Object> result = new LinkedHashMap<>();
|
||||
result.put("enabled", enabled);
|
||||
result.put("outbox_table", outboxTable);
|
||||
result.put("events_written_total", events.get());
|
||||
result.put("write_failures_total", failures.get());
|
||||
return result;
|
||||
}
|
||||
|
||||
static String safeTable(String table) {
|
||||
if (table == null || !table.matches("[A-Za-z][A-Za-z0-9_]*")) {
|
||||
throw new IllegalStateException("Invalid stats projection table: " + table);
|
||||
}
|
||||
return table;
|
||||
}
|
||||
}
|
||||
+11
@@ -9,6 +9,7 @@ import com.common.mapper.SyslogNonNormalMessageMapper;
|
||||
import com.common.service.SyslogNonNormalMessageService;
|
||||
import com.common.service.StatsChangeCaptureService;
|
||||
import com.common.service.DirectStatsProjectionWriter;
|
||||
import com.common.service.DmLargeTextLimiter;
|
||||
import lombok.extern.slf4j.Slf4j;
|
||||
import org.springframework.beans.factory.annotation.Autowired;
|
||||
import org.springframework.beans.factory.annotation.Value;
|
||||
@@ -40,6 +41,9 @@ public class SyslogNonNormalMessageServiceImpl
|
||||
@Autowired
|
||||
private DirectStatsProjectionWriter directStatsProjectionWriter;
|
||||
|
||||
@Autowired(required = false)
|
||||
private DmLargeTextLimiter largeTextLimiter;
|
||||
|
||||
@Value("${dm.non-normal-write.batch-size:500}")
|
||||
private int nonNormalBatchSize;
|
||||
|
||||
@@ -47,6 +51,7 @@ public class SyslogNonNormalMessageServiceImpl
|
||||
@Transactional(rollbackFor = Exception.class)
|
||||
public boolean saveMessage(SyslogNonNormalMessage message) {
|
||||
try {
|
||||
truncateLargeFields(message);
|
||||
// 设置ID(如果未提供)
|
||||
if (message.getId() == null || message.getId().isEmpty()) {
|
||||
message.setId(generateMessageId());
|
||||
@@ -101,6 +106,7 @@ public class SyslogNonNormalMessageServiceImpl
|
||||
try {
|
||||
// 为每条记录设置默认值
|
||||
for (SyslogNonNormalMessage message : messages) {
|
||||
truncateLargeFields(message);
|
||||
if (message.getId() == null || message.getId().isEmpty()) {
|
||||
message.setId(generateMessageId());
|
||||
}
|
||||
@@ -159,10 +165,15 @@ public class SyslogNonNormalMessageServiceImpl
|
||||
}
|
||||
}
|
||||
|
||||
private void truncateLargeFields(SyslogNonNormalMessage message) {
|
||||
if (largeTextLimiter != null) largeTextLimiter.truncateNonNormal(message);
|
||||
}
|
||||
|
||||
@Override
|
||||
@Transactional(rollbackFor = Exception.class)
|
||||
public boolean updateMessage(SyslogNonNormalMessage message) {
|
||||
try {
|
||||
truncateLargeFields(message);
|
||||
SyslogNonNormalMessage oldValue = getMessageById(message.getId());
|
||||
// 设置更新时间
|
||||
message.setUpdateTime(LocalDateTime.now());
|
||||
|
||||
+88
@@ -0,0 +1,88 @@
|
||||
package com.common.util;
|
||||
|
||||
import java.nio.charset.StandardCharsets;
|
||||
import java.security.MessageDigest;
|
||||
|
||||
/** UTF-8 字节预算截断器;标记属于最终存储值的一部分,且永不切断 Unicode 字符。 */
|
||||
public final class Utf8TextTruncator {
|
||||
private static final String MARKER_FORMAT = "...[HB_XDR_TRUNCATED original_utf8_bytes=%d]";
|
||||
|
||||
private Utf8TextTruncator() { }
|
||||
|
||||
public static Result truncate(String text, long maxUtf8Bytes) {
|
||||
if (text == null) return new Result(null, false, 0L, 0L, null);
|
||||
if (maxUtf8Bytes < 0L) throw new IllegalArgumentException("maxUtf8Bytes 不能小于 0");
|
||||
|
||||
byte[] original = text.getBytes(StandardCharsets.UTF_8);
|
||||
long originalBytes = original.length;
|
||||
if (maxUtf8Bytes == 0L || originalBytes <= maxUtf8Bytes) {
|
||||
return new Result(text, false, originalBytes, originalBytes, null);
|
||||
}
|
||||
|
||||
String marker = String.format(MARKER_FORMAT, originalBytes);
|
||||
int markerBytes = marker.getBytes(StandardCharsets.UTF_8).length;
|
||||
if (maxUtf8Bytes < markerBytes) {
|
||||
throw new IllegalArgumentException("UTF-8 截断上限小于截断标记长度: limit="
|
||||
+ maxUtf8Bytes + ", markerBytes=" + markerBytes);
|
||||
}
|
||||
long prefixBudget = maxUtf8Bytes - markerBytes;
|
||||
int end = prefixEnd(text, prefixBudget);
|
||||
String stored = text.substring(0, end) + marker;
|
||||
return new Result(stored, true, originalBytes,
|
||||
stored.getBytes(StandardCharsets.UTF_8).length, sha256(original));
|
||||
}
|
||||
|
||||
private static int prefixEnd(String text, long byteBudget) {
|
||||
long used = 0L;
|
||||
int index = 0;
|
||||
while (index < text.length()) {
|
||||
int codePoint = text.codePointAt(index);
|
||||
int width = utf8Width(codePoint);
|
||||
if (used + width > byteBudget) break;
|
||||
used += width;
|
||||
index += Character.charCount(codePoint);
|
||||
}
|
||||
return index;
|
||||
}
|
||||
|
||||
private static int utf8Width(int codePoint) {
|
||||
if (codePoint <= 0x7f) return 1;
|
||||
if (codePoint <= 0x7ff) return 2;
|
||||
if (codePoint <= 0xffff) return 3;
|
||||
return 4;
|
||||
}
|
||||
|
||||
private static String sha256(byte[] bytes) {
|
||||
try {
|
||||
byte[] digest = MessageDigest.getInstance("SHA-256").digest(bytes);
|
||||
StringBuilder hex = new StringBuilder(digest.length * 2);
|
||||
for (byte item : digest) hex.append(String.format("%02x", item & 0xff));
|
||||
return hex.toString();
|
||||
} catch (Exception impossible) {
|
||||
throw new IllegalStateException("JVM 不支持 SHA-256", impossible);
|
||||
}
|
||||
}
|
||||
|
||||
public static final class Result {
|
||||
private final String value;
|
||||
private final boolean truncated;
|
||||
private final long originalUtf8Bytes;
|
||||
private final long storedUtf8Bytes;
|
||||
private final String originalSha256;
|
||||
|
||||
Result(String value, boolean truncated, long originalUtf8Bytes,
|
||||
long storedUtf8Bytes, String originalSha256) {
|
||||
this.value = value;
|
||||
this.truncated = truncated;
|
||||
this.originalUtf8Bytes = originalUtf8Bytes;
|
||||
this.storedUtf8Bytes = storedUtf8Bytes;
|
||||
this.originalSha256 = originalSha256;
|
||||
}
|
||||
|
||||
public String getValue() { return value; }
|
||||
public boolean isTruncated() { return truncated; }
|
||||
public long getOriginalUtf8Bytes() { return originalUtf8Bytes; }
|
||||
public long getStoredUtf8Bytes() { return storedUtf8Bytes; }
|
||||
public String getOriginalSha256() { return originalSha256; }
|
||||
}
|
||||
}
|
||||
Reference in New Issue
Block a user