Logstash Doris output plugin

介绍

Logstash 是一个日志ETL框架（采集，预处理，发送到存储系统），它支持自定义输出插件将数据写入存储系统，Logstash Doris output plugin 是输出到 Doris 的插件。

Logstash Doris output plugin 调用 Doris Stream Load HTTP 接口将数据实时写入 Doris，提供多线程并发，失败重试，自定义 Stream Load 格式和参数，输出写入速度等能力。

使用 Logstash Doris output plugin 主要有三个步骤：

1. 将插件安装到 Logstash 中
2. 配置 Doris 输出地址和其他参数
3. 启动 Logstash 将数据实时写入 Doris

安装

获取插件

可以从官网下载或者自行从源码编译 Logstash Doris output plugin。

• 从官网下载

  • 不包含依赖的安装包 https://apache-doris-releases.oss-accelerate.aliyuncs.com/logstash-output-doris-1.0.0.gem
  • 包含依赖的安装包 https://apache-doris-releases.oss-accelerate.aliyuncs.com/logstash-output-doris-1.0.0.zip
• 从源码编译

cd extension/logstash/
gem build logstash-output-doris.gemspec

安装插件

• 普通安装

${LOGSTASH_HOME} 是 Logstash 的安装目录，运行它下面的 bin/logstash-plugin 命令安装插件

${LOGSTASH_HOME}/bin/logstash-plugin install logstash-output-doris-1.0.0.gem
Validating logstash-output-doris-1.0.0.gem
Installing logstash-output-doris
Installation successful

普通安装模式会自动安装插件依赖的 ruby 模块，对于网络不通的情况会卡住无法完成，这种情况下可以下载包含依赖的zip安装包进行完全离线安装，注意需要用 file:// 指定本地文件系统。

• 离线安装

${LOGSTASH_HOME}/bin/logstash-plugin install file:///tmp/logstash-output-doris-1.0.0.zip
Installing file: logstash-output-doris-1.0.0.zip
Resolving dependencies.........................
Install successful

参数配置

Logstash Doris output plugin 的配置如下：

使用示例

TEXT 日志采集示例

该示例以 Doris FE 的日志为例展示 TEXT 日志采集。

1. 数据

FE 日志文件一般位于 Doris 安装目录下的 fe/log/fe.log 文件，是典型的 Java 程序日志，包括时间戳，日志级别，线程名，代码位置，日志内容等字段。不仅有正常的日志，还有带 stacktrace 的异常日志，stacktrace 是跨行的，日志采集存储需要把主日志和 stacktrace 组合成一条日志。

2024-07-08 21:18:01,432 INFO (Statistics Job Appender|61) [StatisticsJobAppender.runAfterCatalogReady():70] Stats table not available, skip
2024-07-08 21:18:53,710 WARN (STATS_FETCH-0|208) [StmtExecutor.executeInternalQuery():3332] Failed to run internal SQL: OriginStatement{originStmt='SELECT * FROM __internal_schema.column_statistics WHERE part_id is NULL  ORDER BY update_time DESC LIMIT 500000', idx=0}
org.apache.doris.common.UserException: errCode = 2, detailMessage = tablet 10031 has no queryable replicas. err: replica 10032's backend 10008 does not exist or not alive
        at org.apache.doris.planner.OlapScanNode.addScanRangeLocations(OlapScanNode.java:931) ~[doris-fe.jar:1.2-SNAPSHOT]
        at org.apache.doris.planner.OlapScanNode.computeTabletInfo(OlapScanNode.java:1197) ~[doris-fe.jar:1.2-SNAPSHOT]

2. 建表

表结构包括日志的产生时间，采集时间，主机名，日志文件路径，日志类型，日志级别，线程名，代码位置，日志内容等字段。

CREATE TABLE `doris_log` (
  `log_time` datetime NULL COMMENT 'log content time',
  `collect_time` datetime NULL COMMENT 'log agent collect time',
  `host` text NULL COMMENT 'hostname or ip',
  `path` text NULL COMMENT 'log file path',
  `type` text NULL COMMENT 'log type',
  `level` text NULL COMMENT 'log level',
  `thread` text NULL COMMENT 'log thread',
  `position` text NULL COMMENT 'log code position',
  `message` text NULL COMMENT 'log message',
  INDEX idx_host (`host`) USING INVERTED COMMENT '',
  INDEX idx_path (`path`) USING INVERTED COMMENT '',
  INDEX idx_type (`type`) USING INVERTED COMMENT '',
  INDEX idx_level (`level`) USING INVERTED COMMENT '',
  INDEX idx_thread (`thread`) USING INVERTED COMMENT '',
  INDEX idx_position (`position`) USING INVERTED COMMENT '',
  INDEX idx_message (`message`) USING INVERTED PROPERTIES("parser" = "unicode", "support_phrase" = "true") COMMENT ''
) ENGINE=OLAP
DUPLICATE KEY(`log_time`)
COMMENT 'OLAP'
PARTITION BY RANGE(`log_time`) ()
DISTRIBUTED BY RANDOM BUCKETS 10
PROPERTIES (
"replication_num" = "1",
"dynamic_partition.enable" = "true",
"dynamic_partition.time_unit" = "DAY",
"dynamic_partition.start" = "-7",
"dynamic_partition.end" = "1",
"dynamic_partition.prefix" = "p",
"dynamic_partition.buckets" = "10",
"dynamic_partition.create_history_partition" = "true",
"compaction_policy" = "time_series"
);

3. Logstash 配置

Logstash 主要有两类配置文件，一类是整个 Logstash 的配置文件，另一类是某个日志采集的配置文件。

整个 Logstash 的配置文件通常在 config/logstash.yml，为了提升写入 Doris 的性能需要修改 batch 大小和攒批时间，对于平均每条i几百字节的日志，推荐 100 万行和 10s 。

pipeline.batch.size: 1000000
pipeline.batch.delay: 10000

某个日志采集的配置文件如 logstash_doris_log.conf 主要由 3 部分组成，分别对应 ETL 的各个部分：

1. input 负责读取原始数据
2. filter 负责做数据转换
3. output 负责将数据输出

# 1. input 负责读取原始数据
# file input 是一个 input plugin，可以配置读取的日志文件路径，通过 multiline codec 将非时间开头的行拼接到上一行后面，实现 stacktrace 和主日志合并的效果。file input 会将日志内容保存在 @message 字段中，另外还有一些元数据字段比如 host，log.file.path，这里我们还通过 add_field 手动添加了一个字段 type，它的值为 fe.log 。
input {
    file {
        path => "/mnt/disk2/xiaokang/opt/doris_master/fe/log/fe.log"
        add_field => {"type" => "fe.log"}
        codec => multiline {
            # valid line starts with timestamp
            pattern => "^%{TIMESTAMP_ISO8601} "
            # any line not starting with a timestamp should be merged with the previous line
            negate => true
            what => "previous"
        }
    }
}
# 2. filter 部分负责数据转换
# grok 是一个常用的数据转换插件，它内置了一些常见的pattern 比如 TIMESTAMP_ISO8601 解析时间戳，还支持写正则表达式提取字段。
filter {
    grok {
        match => {
            # parse log_time, level, thread, position fields from message
            "message" => "%{TIMESTAMP_ISO8601:log_time} (?<level>[A-Z]+) \((?<thread>[^\[]*)\) \[(?<position>[^\]]*)\]"
        }
    }
}
# 3. output 部分负责数据输出
# doris output 将数据输出到 Doris，使用的是 Stream Load HTTP 接口。通过 headers 参数指定了 Stream Load 的数据格式为 JSON，通过 mapping 参数指定 Logstash 字段到 JSON 字段的映射。由于 headers 指定了 "format" => "json"，Stream Load 会自动解析 JSON 字段写入对应的 Doris 表的字段。
output {
    doris {
        http_hosts => ["http://localhost:8630"]
        user => "root"
        password => ""
        db => "log_db"
        table => "doris_log"
        headers => {
          "format" => "json"
          "read_json_by_line" => "true"
          "load_to_single_tablet" => "true"
        }
        mapping => {
          "log_time" => "%{log_time}"
          "collect_time" => "%{@timestamp}"
          "host" => "%{[host][name]}"
          "path" => "%{[log][file][path]}"
          "type" => "%{type}"
          "level" => "%{level}"
          "thread" => "%{thread}"
          "position" => "%{position}"
          "message" => "%{message}"
        }
        log_request => true
    }
}

4. 运行 Logstash

${LOGSTASH_HOME}/bin/logstash -f config/logstash_doris_log.conf
# log_request 为 true 时日志会输出每次 Stream Load 的请求参数和响应结果
[2024-07-08T22:35:34,772][INFO ][logstash.outputs.doris   ][main][e44d2a24f17d764647ce56f5fed24b9bbf08d3020c7fddcc3298800daface80a] doris stream load response:
{
    "TxnId": 45464,
    "Label": "logstash_log_db_doris_log_20240708_223532_539_6c20a0d1-dcab-4b8e-9bc0-76b46a929bd1",
    "Comment": "",
    "TwoPhaseCommit": "false",
    "Status": "Success",
    "Message": "OK",
    "NumberTotalRows": 452,
    "NumberLoadedRows": 452,
    "NumberFilteredRows": 0,
    "NumberUnselectedRows": 0,
    "LoadBytes": 277230,
    "LoadTimeMs": 1797,
    "BeginTxnTimeMs": 0,
    "StreamLoadPutTimeMs": 18,
    "ReadDataTimeMs": 9,
    "WriteDataTimeMs": 1758,
    "CommitAndPublishTimeMs": 18
}
# 默认每隔 10s 会日志输出速度信息，包括自启动以来的数据量（MB 和 ROWS），总速度（MB/s 和 R/S），最近 10s 速度
[2024-07-08T22:35:38,285][INFO ][logstash.outputs.doris   ][main] total 11 MB 18978 ROWS, total speed 0 MB/s 632 R/s, last 10 seconds speed 1 MB/s 1897 R/s

JSON 日志采集示例

该样例以 github events archive 的数据为例展示 JSON 日志采集。

1. 数据

github events archive 是 github 用户操作事件的归档数据，格式是 JSON，可以从 https://www.gharchive.org/ 下载，比如下载 2024年1月1日15点的数据。

wget https://data.gharchive.org/2024-01-01-15.json.gz

下面是一条数据样例，实际一条数据一行，这里为了方便展示进行了格式化。

{
  "id": "37066529221",
  "type": "PushEvent",
  "actor": {
    "id": 46139131,
    "login": "Bard89",
    "display_login": "Bard89",
    "gravatar_id": "",
    "url": "https://api.github.com/users/Bard89",
    "avatar_url": "https://avatars.githubusercontent.com/u/46139131?"
  },
  "repo": {
    "id": 780125623,
    "name": "Bard89/talk-to-me",
    "url": "https://api.github.com/repos/Bard89/talk-to-me"
  },
  "payload": {
    "repository_id": 780125623,
    "push_id": 17799451992,
    "size": 1,
    "distinct_size": 1,
    "ref": "refs/heads/add_mvcs",
    "head": "f03baa2de66f88f5f1754ce3fa30972667f87e81",
    "before": "85e6544ede4ae3f132fe2f5f1ce0ce35a3169d21"
  },
  "public": true,
  "created_at": "2024-04-01T23:00:00Z"
}

2. Doris 建表

CREATE DATABASE log_db;
USE log_db;
CREATE TABLE github_events
(
  `created_at` DATETIME,
  `id` BIGINT,
  `type` TEXT,
  `public` BOOLEAN,
  `actor.id` BIGINT,
  `actor.login` TEXT,
  `actor.display_login` TEXT,
  `actor.gravatar_id` TEXT,
  `actor.url` TEXT,
  `actor.avatar_url` TEXT,
  `repo.id` BIGINT,
  `repo.name` TEXT,
  `repo.url` TEXT,
  `payload` TEXT,
  `host` TEXT,
  `path` TEXT,
  INDEX `idx_id` (`id`) USING INVERTED,
  INDEX `idx_type` (`type`) USING INVERTED,
  INDEX `idx_actor.id` (`actor.id`) USING INVERTED,
  INDEX `idx_actor.login` (`actor.login`) USING INVERTED,
  INDEX `idx_repo.id` (`repo.id`) USING INVERTED,
  INDEX `idx_repo.name` (`repo.name`) USING INVERTED,
  INDEX `idx_host` (`host`) USING INVERTED,
  INDEX `idx_path` (`path`) USING INVERTED,
  INDEX `idx_payload` (`payload`) USING INVERTED PROPERTIES("parser" = "unicode", "support_phrase" = "true")
)
ENGINE = OLAP
DUPLICATE KEY(`created_at`)
PARTITION BY RANGE(`created_at`) ()
DISTRIBUTED BY RANDOM BUCKETS 10
PROPERTIES (
"replication_num" = "1",
"compaction_policy" = "time_series",
"enable_single_replica_compaction" = "true",
"dynamic_partition.enable" = "true",
"dynamic_partition.create_history_partition" = "true",
"dynamic_partition.time_unit" = "DAY",
"dynamic_partition.start" = "-30",
"dynamic_partition.end" = "1",
"dynamic_partition.prefix" = "p",
"dynamic_partition.buckets" = "10",
"dynamic_partition.replication_num" = "1"
);

3. Logstash 配置

这个配置文件和之前 TEXT 日志采集不同的有下面几点：

1. file input 的 codec 参数是 json，Logstash 会将每一行文本当作 JSON 格式解析，解析出来的字段用于后续处理
2. 没有用 filter plugin，因为不需要额外的处理转换

input {
    file {
        path => "/tmp/github_events/2024-04-01-23.json"
        codec => json
    }
}
output {
    doris {
        http_hosts => ["http://fe1:8630", "http://fe2:8630", "http://fe3:8630"]
        user => "root"
        password => ""
        db => "log_db"
        table => "github_events"
        headers => {
          "format" => "json"
          "read_json_by_line" => "true"
          "load_to_single_tablet" => "true"
        }
        mapping => {
          "created_at" => "%{created_at}"
          "id" => "%{id}"
          "type" => "%{type}"
          "public" => "%{public}"
          "actor.id" => "%{[actor][id]}"
          "actor.login" => "%{[actor][login]}"
          "actor.display_login" => "%{[actor][display_login]}"
          "actor.gravatar_id" => "%{[actor][gravatar_id]}"
          "actor.url" => "%{[actor][url]}"
          "actor.avatar_url" => "%{[actor][avatar_url]}"
          "repo.id" => "%{[repo][id]}"
          "repo.name" => "%{[repo][name]}"
          "repo.url" => "%{[repo][url]}"
          "payload" => "%{[payload]}"
          "host" => "%{[host][name]}"
          "path" => "%{[log][file][path]}"
        }
        log_request => true
    }
}

4. 运行 Logstash

${LOGSTASH_HOME}/bin/logstash -f logstash_github_events.conf