StreamSets数据收集器似乎读取了不正确的日期时间值。
我尝试从Confluent阅读简单主题：当我使用Landoop Kafka主题检查datetime值（以毫秒为单位）时 - 它显示正确的日期时间，但是当我在StreamSet中使用Kafka Consumer 0.10.0.0读取它时 - 它给了我一个3小时的日期时间小20分钟。我的实际时区是GMT + 03:00。
我的SDC设置有正确的时区，服务器操作系统也有正确的时间，甚至时间：SDC功能中的now（）给出正确的结果！
任何猜测为什么？
更新 - 导出我的工作流程
{
"pipelineConfig" : {
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"value" : "STANDALONE"
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"name" : "deliveryGuarantee",
"value" : "AT_LEAST_ONCE"
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"value" : "${jvm:maxMemoryMB() * 0.65}"
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"name" : "memoryLimitExceeded",
"value" : "STOP_PIPELINE"
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"name" : "notifyOnStates",
"value" : [ "RUN_ERROR", "STOPPED", "FINISHED" ]
}, {
"name" : "emailIDs",
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"name" : "constants",
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"value" : "streamsets-datacollector-basic-lib::com_streamsets_pipeline_stage_destination_recordstolocalfilesystem_ToErrorLocalFSDTarget::1"
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"name" : "clusterSlaveJavaOpts",
"value" : "-XX:+UseConcMarkSweepGC -XX:+UseParNewGC -Dlog4j.debug"
}, {
"name" : "clusterLauncherEnv",
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"value" : "\\r\\n"
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}, {
"name" : "kafkaConfigBean.dataFormatConfig.jsonContent",
"value" : "MULTIPLE_OBJECTS"
}, {
"name" : "kafkaConfigBean.dataFormatConfig.jsonMaxObjectLen",
"value" : 4096
}, {
"name" : "kafkaConfigBean.dataFormatConfig.csvFileFormat",
"value" : "CSV"
}, {
"name" : "kafkaConfigBean.dataFormatConfig.csvHeader",
"value" : "NO_HEADER"
}, {
"name" : "kafkaConfigBean.dataFormatConfig.csvMaxObjectLen",
"value" : 1024
}, {
"name" : "kafkaConfigBean.dataFormatConfig.csvAllowExtraColumns",
"value" : false
}, {
"name" : "kafkaConfigBean.dataFormatConfig.csvExtraColumnPrefix",
"value" : "_extra_"
}, {
"name" : "kafkaConfigBean.dataFormatConfig.csvCustomDelimiter",
"value" : "|"
}, {
"name" : "kafkaConfigBean.dataFormatConfig.csvCustomEscape",
"value" : "\\"
}, {
"name" : "kafkaConfigBean.dataFormatConfig.csvCustomQuote",
"value" : "\""
}, {
"name" : "kafkaConfigBean.dataFormatConfig.csvEnableComments",
"value" : false
}, {
"name" : "kafkaConfigBean.dataFormatConfig.csvCommentMarker",
"value" : "#"
}, {
"name" : "kafkaConfigBean.dataFormatConfig.csvIgnoreEmptyLines",
"value" : true
}, {
"name" : "kafkaConfigBean.dataFormatConfig.csvRecordType",
"value" : "LIST_MAP"
}, {
"name" : "kafkaConfigBean.dataFormatConfig.csvSkipStartLines",
"value" : 0
}, {
"name" : "kafkaConfigBean.dataFormatConfig.parseNull",
"value" : false
}, {
"name" : "kafkaConfigBean.dataFormatConfig.nullConstant",
"value" : "\\\\N"
}, {
"name" : "kafkaConfigBean.dataFormatConfig.xmlRecordElement",
"value" : null
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"name" : "kafkaConfigBean.dataFormatConfig.includeFieldXpathAttributes",
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}, {
"name" : "kafkaConfigBean.dataFormatConfig.xPathNamespaceContext",
"value" : [ ]
}, {
"name" : "kafkaConfigBean.dataFormatConfig.outputFieldAttributes",
"value" : false
}, {
"name" : "kafkaConfigBean.dataFormatConfig.xmlMaxObjectLen",
"value" : 4096
}, {
"name" : "kafkaConfigBean.dataFormatConfig.logMode",
"value" : "COMMON_LOG_FORMAT"
}, {
"name" : "kafkaConfigBean.dataFormatConfig.logMaxObjectLen",
"value" : 1024
}, {
"name" : "kafkaConfigBean.dataFormatConfig.retainOriginalLine",
"value" : false
}, {
"name" : "kafkaConfigBean.dataFormatConfig.customLogFormat",
"value" : "%h %l %u %t \"%r\" %>s %b"
}, {
"name" : "kafkaConfigBean.dataFormatConfig.regex",
"value" : "^(\\S+) (\\S+) (\\S+) \\[([\\w:/]+\\s[+\\-]\\d{4})\\] \"(\\S+) (\\S+) (\\S+)\" (\\d{3}) (\\d+)"
}, {
"name" : "kafkaConfigBean.dataFormatConfig.fieldPathsToGroupName",
"value" : [ {
"fieldPath" : "/",
"group" : 1
} ]
}, {
"name" : "kafkaConfigBean.dataFormatConfig.grokPatternDefinition",
"value" : null
}, {
"name" : "kafkaConfigBean.dataFormatConfig.grokPattern",
"value" : "%{COMMONAPACHELOG}"
}, {
"name" : "kafkaConfigBean.dataFormatConfig.onParseError",
"value" : "ERROR"
}, {
"name" : "kafkaConfigBean.dataFormatConfig.maxStackTraceLines",
"value" : 50
}, {
"name" : "kafkaConfigBean.dataFormatConfig.enableLog4jCustomLogFormat",
"value" : false
}, {
"name" : "kafkaConfigBean.dataFormatConfig.log4jCustomLogFormat",
"value" : "%r [%t] %-5p %c %x - %m%n"
}, {
"name" : "kafkaConfigBean.dataFormatConfig.avroSchemaSource",
"value" : "REGISTRY"
}, {
"name" : "kafkaConfigBean.dataFormatConfig.avroSchema",
"value" : null
}, {
"name" : "kafkaConfigBean.dataFormatConfig.schemaRegistryUrls",
"value" : [ "http://test-kafka01.mytest.com:8081" ]
}, {
"name" : "kafkaConfigBean.dataFormatConfig.schemaLookupMode",
"value" : "AUTO"
}, {
"name" : "kafkaConfigBean.dataFormatConfig.subject",
"value" : null
}, {
"name" : "kafkaConfigBean.dataFormatConfig.schemaId",
"value" : null
}, {
"name" : "kafkaConfigBean.dataFormatConfig.protoDescriptorFile",
"value" : null
}, {
"name" : "kafkaConfigBean.dataFormatConfig.messageType",
"value" : null
}, {
"name" : "kafkaConfigBean.dataFormatConfig.isDelimited",
"value" : true
}, {
"name" : "kafkaConfigBean.dataFormatConfig.binaryMaxObjectLen",
"value" : 1024
}, {
"name" : "kafkaConfigBean.dataFormatConfig.datagramMode",
"value" : "SYSLOG"
}, {
"name" : "kafkaConfigBean.dataFormatConfig.typesDbPath",
"value" : null
}, {
"name" : "kafkaConfigBean.dataFormatConfig.convertTime",
"value" : false
}, {
"name" : "kafkaConfigBean.dataFormatConfig.excludeInterval",
"value" : true
}, {
"name" : "kafkaConfigBean.dataFormatConfig.authFilePath",
"value" : null
}, {
"name" : "kafkaConfigBean.dataFormatConfig.wholeFileMaxObjectLen",
"value" : 8192
}, {
"name" : "kafkaConfigBean.dataFormatConfig.rateLimit",
"value" : "-1"
}, {
"name" : "kafkaConfigBean.dataFormatConfig.verifyChecksum",
"value" : false
}, {
"name" : "kafkaConfigBean.dataFormat",
"value" : "AVRO"
}, {
"name" : "kafkaConfigBean.metadataBrokerList",
"value" : "test-kafka01:9092,test-kafka02:9092,test-kafka03:9092"
}, {
"name" : "kafkaConfigBean.zookeeperConnect",
"value" : "test-kafka01:2181,test-kafka02:2181,test-kafka03:2181"
}, {
"name" : "kafkaConfigBean.consumerGroup",
"value" : "connector_elastic"
}, {
"name" : "kafkaConfigBean.topic",
"value" : "test_data"
}, {
"name" : "kafkaConfigBean.produceSingleRecordPerMessage",
"value" : false
}, {
"name" : "kafkaConfigBean.maxBatchSize",
"value" : 1000
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"name" : "kafkaConfigBean.maxRatePerPartition",
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"value" : "CONFLUENT"
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"name" : "kafkaConfigBean.kafkaConsumerConfigs",
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"name" : "brokerPort",
"value" : 9092
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"name" : "topic",
"value" : "myTopic"
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"library" : "streamsets-datacollector-basic-lib",
"stageName" : "com_streamsets_pipeline_stage_destination_localfilesystem_LocalFileSystemDTarget",
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"value" : "Europe/Moscow"
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"value" : "${time:now()}"
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"value" : 0
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"name" : "configs.maxFileSize",
"value" : 0
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"name" : "configs.idleTimeout",
"value" : "${1 * HOURS}"
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"value" : "NONE"
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"value" : "${1 * HOURS}"
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"value" : "MD5"
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}, {
"name" : "stageOnRecordError",
"value" : "TO_ERROR"
}, {
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"value" : [ ]
}, {
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"value" : [ ]
} ],
"uiInfo" : {
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} ],
"errorStage" : {
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"library" : "streamsets-datacollector-basic-lib",
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"stageVersion" : "1",
"configuration" : [ {
"name" : "directory",
"value" : "/tmp/data_monitor/out/error"
}, {
"name" : "uniquePrefix",
"value" : "sdc-${sdc:id()}"
}, {
"name" : "rotationIntervalSecs",
"value" : "${1 * HOURS}"
}, {
"name" : "maxFileSizeMbs",
"value" : 512
} ],
"uiInfo" : {
"description" : "",
"label" : "Error Records - Write to File",
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},
"statsAggregatorStage" : {
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"library" : "streamsets-datacollector-basic-lib",
"stageName" : "com_streamsets_pipeline_stage_destination_devnull_StatsDpmDirectlyDTarget",
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"valid" : true,
"issues" : {
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},
"previewable" : true
},
"pipelineRules" : {
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"metricElement" : "COUNTER_COUNT",
"condition" : "${value() > 100}",
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"timestamp" : 1508152340733,
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}, {
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"condition" : "${value() > 100}",
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"uuid" : "6ab2f9cf-0043-48e7-8e5f-1a3d2ec86d4d",
"configuration" : [ {
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"value" : [ ]
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} ],
"configIssues" : [ ],
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},
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}
答案 0 :(得分：1)
为了记录，我们在其他地方发现了这一点。这与Java date patterns有关。
使用像2017-10-20 13:15:33.611796这样的表达式解析一个毫秒的字符串（如${time:extractDateFromString(record:value("/ts"),"yyyy-MM-dd hh:mm:ss.SSSSSS")}）并不像您预期的那样工作。 S表示毫秒，因此611,796微秒被解释为611,796毫秒，611秒（仅超过10分钟）被添加到时间，导致Date对象的值为2017-10-20 01:25:44.796。
修剪传入字符串的微秒，如下所示：${time:extractDateFromString(str:substring(record:value("/ts"), 0, 23),"yyyy-MM-dd hh:mm:ss.SSS")}有效。如果${str:substring(record:value("/ts"), 23, 26)}
答案 1 :(得分：0)
在Docker for Mac中运行服务时遇到了类似的问题。存在一个长期存在的已知问题，其中VM的系统时间偏离主机的系统时间，这可以通过重启Docker来解决。这也可能会影响你吗？