blocks|key|4100220|text|假设您有一个类似于一个生日的人的模式，并且您想要拆分生日：|type|unstyled|depth|inlineStyleRanges|entityRanges|data|4100221|{
++"name":+"person",
++"namespace":+"nifi",
++"type":+"record",
++"fields":+[
++++{+"name":+"first_name",+"type":+"string"+},
++++{+"name":+"last_name",+"type":+"string"+},
++++{+"name":+"birthday",+"type":+"string"+}
++]
}|code-block|syntax|javascript|4100222|您需要修改架构，使其具有要添加的字段：|4100223|{
++"name":+"person",
++"namespace":+"nifi",
++"type":+"record",
++"fields":+[
++++{+"name":+"first_name",+"type":+"string"+},
++++{+"name":+"last_name",+"type":+"string"+},
++++{+"name":+"birthday",+"type":+"string"+},
++++{+"name":+"birthday_year",+"type":+["null",+"string"]+},
++++{+"name":+"birthday_month",+"type":+["null",+"string"]+},
++++{+"name":+"birthday_day",+"type":+["null",+"string"]+}
++]
}|4100224|假设输入记录包含以下文本：|4100225|bryan,bende,1980-01-01|4100226|我们可以使用带有CsvReader和CsvWriter的UpdateRecord，UpdateRecord可以通过解析原始的生日字段来填充我们想要的三个字段。|4100227|​|4100228|📷|atomic|offset|length|4100229|4100230|如果我们将输出发送到LogAttribute，我们现在应该看到以下内容：|4100231|first_name,last_name,birthday,birthday_year,birthday_month,birthday_day
bryan,bende,1980-01-01,1980,01,01|4100232|以下是指向记录路径指南的链接，了解有关toDate和格式函数的详细信息：|4100233|https://nifi.apache.org/docs/nifi-docs/html/record-path-guide.html|4100234|entityMap|0|IMAGE|mutability|IMMUTABLE|imageUrl|https://ask.qcloudimg.com/http-save/yehe-900000/7320f2c724a2f816bfdefd5d2ccff5be.png|imageAlt|1|LINK|MUTABLE|url^0|0|0|0|0|0|0|0|0|0|1|0|0|0|0|0|0|0|1U|1|0^^$0|@$1|2|3|4|5|6|7|1J|8|@]|9|@]|A|$]]|$1|B|3|C|5|D|7|1K|8|@]|9|@]|A|$E|F]]|$1|G|3|H|5|6|7|1L|8|@]|9|@]|A|$]]|$1|I|3|J|5|D|7|1M|8|@]|9|@]|A|$E|F]]|$1|K|3|L|5|6|7|1N|8|@]|9|@]|A|$]]|$1|M|3|N|5|D|7|1O|8|@]|9|@]|A|$E|F]]|$1|O|3|P|5|6|7|1P|8|@]|9|@]|A|$]]|$1|Q|3|R|5|6|7|1Q|8|@]|9|@]|A|$]]|$1|S|3|T|5|U|7|1R|8|@]|9|@$V|1S|W|1T|1|1U]]|A|$]]|$1|X|3|R|5|6|7|1V|8|@]|9|@]|A|$]]|$1|Y|3|Z|5|6|7|1W|8|@]|9|@]|A|$]]|$1|10|3|11|5|D|7|1X|8|@]|9|@]|A|$E|F]]|$1|12|3|13|5|6|7|1Y|8|@]|9|@]|A|$]]|$1|14|3|15|5|6|7|1Z|8|@]|9|@$V|20|W|21|1|22]]|A|$]]|$1|16|3|-4|5|6|7|23|8|@]|9|@]|A|$]]]|17|$18|$5|19|1A|1B|A|$1C|1D|1E|-4]]|1F|$5|1G|1A|1H|A|$1I|15]]]]

Lets say you have a schema like this for a person with a birthday and you want to split out the birthday:

<pre><code>{
 "name": "person",
 "namespace": "nifi",
 "type": "record",
 "fields": [
 { "name": "first_name", "type": "string" },
 { "name": "last_name", "type": "string" },
 { "name": "birthday", "type": "string" }
 ]
}
</code></pre>

You would need to modify the schema so it had the fields you want to add:

<pre><code>{
 "name": "person",
 "namespace": "nifi",
 "type": "record",
 "fields": [
 { "name": "first_name", "type": "string" },
 { "name": "last_name", "type": "string" },
 { "name": "birthday", "type": "string" },
 { "name": "birthday_year", "type": ["null", "string"] },
 { "name": "birthday_month", "type": ["null", "string"] },
 { "name": "birthday_day", "type": ["null", "string"] }
 ]
}
</code></pre>

Lets say the input record has the following text:

<pre><code>bryan,bende,1980-01-01
</code></pre>

We can use UpdateRecord with a CsvReader and CsvWriter, and UpdateRecord can populate the three fields we want by parsing the original birthday field.

<a href="https://i.stack.imgur.com/zAzBg.png" rel="noreferrer"><img src="https://i.stack.imgur.com/zAzBg.png" alt="enter image description here"></a>

If we send the output to LogAttribute we should see the following now:

<pre><code>first_name,last_name,birthday,birthday_year,birthday_month,birthday_day
bryan,bende,1980-01-01,1980,01,01
</code></pre>

Here is the link to the record path guide for details on the toDate and format functions:

<a href="https://nifi.apache.org/docs/nifi-docs/html/record-path-guide.html" rel="noreferrer">https://nifi.apache.org/docs/nifi-docs/html/record-path-guide.html</a>

blocks|key|4100262|text|为此，您可以使用UpdateRecord，假设您的输入记录具有名为"myDate“的date列，您将Replacement+Value+Strategy设置为Record+Path+Value，并且您的用户定义属性可能如下所示：|type|unstyled|depth|inlineStyleRanges|offset|length|style|CODE|entityRanges|data|4100263|/day+++format(/myDate,+"dd")+/month++format(/myDate,+"MMM")+/year+++format(/myDate,+"YYYY")|4100264|您的输出模式将如下所示：|4100265|{
+"namespace":+"nifi",
+"name":+"myRecord",
+"type":+"record",
+"fields":+[
++{"name":+"day","type":+"int"},
++{"name":+"month","type":+"string"},
++{"name":+"year","type":+"int"}
+]
}|code-block|syntax|javascript|4100266|entityMap^0|1E|Q|27|H|0|0|2J|0|0|0^^$0|@$1|2|3|4|5|6|7|Q|8|@$9|R|A|S|B|C]|$9|T|A|U|B|C]]|D|@]|E|$]]|$1|F|3|G|5|6|7|V|8|@$9|W|A|X|B|C]]|D|@]|E|$]]|$1|H|3|I|5|6|7|Y|8|@]|D|@]|E|$]]|$1|J|3|K|5|L|7|Z|8|@]|D|@]|E|$M|N]]|$1|O|3|-4|5|6|7|10|8|@]|D|@]|E|$]]]|P|$]]

You can use UpdateRecord for this, assuming your input record has the date column called "myDate", you'd set the <code>Replacement Value Strategy</code> to <code>Record Path Value</code>, and your user-defined properties might look something like:

<code>/day format(/myDate, "dd")
/month format(/myDate, "MMM")
/year format(/myDate, "YYYY")</code>

Your output schema would look like this:

<pre><code>{
 "namespace": "nifi",
 "name": "myRecord",
 "type": "record",
 "fields": [
 {"name": "day","type": "int"},
 {"name": "month","type": "string"},
 {"name": "year","type": "int"}
 ]
}
</code></pre>

Each of my flow file contains 2000 records. I would like to parse 01/01/2000 into a column year = 2000, column month = Jan and column day = 01

i.e. the input column 01/01/2000 into 3 values separated by commas 01,Jan,2000

How do I parse a date field and generate a date in string format in NiFi

翻译质量差，导致语言生硬或混乱。

没有提供实际的解决方法或示例。

解答不清晰，无法理解或解决问题。

页面排版不美观，阅读体验差。

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我的每个流文件包含2000条记录。我想将01/ 01 /2000解析为列year = 2000，列month = Jan和列day =01即，将输入列01/ 01 /2000分成由逗号01分隔的3个值，2000年1月

问如何在NiFi中解析日期字段并生成字符串格式的日期
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问如何在NiFi中解析日期字段并生成字符串格式的日期
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