blocks|key|822488|text|替换所有整数列和长列|type|unstyled|depth|inlineStyleRanges|entityRanges|data|822489|df.na.fill(0)
++.show(false)|code-block|syntax|javascript|822490|用特定列替换|822491|df.na.fill(0,Array("population"))
++.show(false)|822492|字符串类型所有列|822493|df.na.fill("")
++.show(false)|822494|特定列|822495|df.na.fill("unknown",Array("city"))
++.na.fill("",Array("type"))
++.show(false)|822496|entityMap^0|0|0|0|0|0|0|0|0^^$0|@$1|2|3|4|5|6|7|U|8|@]|9|@]|A|$]]|$1|B|3|C|5|D|7|V|8|@]|9|@]|A|$E|F]]|$1|G|3|H|5|6|7|W|8|@]|9|@]|A|$]]|$1|I|3|J|5|D|7|X|8|@]|9|@]|A|$E|F]]|$1|K|3|L|5|6|7|Y|8|@]|9|@]|A|$]]|$1|M|3|N|5|D|7|Z|8|@]|9|@]|A|$E|F]]|$1|O|3|P|5|6|7|10|8|@]|9|@]|A|$]]|$1|Q|3|R|5|D|7|11|8|@]|9|@]|A|$E|F]]|$1|S|3|-4|5|6|7|12|8|@]|9|@]|A|$]]]|T|$]]

Replace all integer and long columns
<pre><code>df.na.fill(0)
 .show(false)
</code></pre>
Replace with specific columns
<pre><code>df.na.fill(0,Array(&quot;population&quot;))
 .show(false)
</code></pre>
String type all columns
<pre><code>df.na.fill(&quot;&quot;)
 .show(false)
</code></pre>
Specific columns
<pre><code>df.na.fill(&quot;unknown&quot;,Array(&quot;city&quot;))
 .na.fill(&quot;&quot;,Array(&quot;type&quot;))
 .show(false)
</code></pre>

blocks|key|679086|text|DataFrame+na填充|type|unstyled|depth|inlineStyleRanges|entityRanges|offset|length|data|679087|类DataFrame|679088|对于您的问题，每一行都有新值。|679089|import+org.apache.spark.sql.SparkSession
import+org.apache.spark.sql.functions._
import+spark.implicits._
val+df1+=+Seq((0.5f,+"v1"),+(0.2f,+"v2"),+(1f,+"v3"),+(4f,+"v4"))
++.toDF("prob",+"column_field")
df1.show(false)
/*
%2B----%2B------------%2B
%7Cprob%7Ccolumn_field%7C
%2B----%2B------------%2B
%7C0.5+%7Cv1++++++++++%7C
%7C0.2+%7Cv2++++++++++%7C
%7C1.0+%7Cv3++++++++++%7C
%7C4.0+%7Cv4++++++++++%7C
%2B----%2B------------%2B
*/
val+resDF+=+df1.withColumn(
++"column_field",
++when(col("prob")+<=+0.5f,+"s")
++++.otherwise("n")
)

resDF.show(false)
/*
%2B----%2B------------%2B
%7Cprob%7Ccolumn_field%7C
%2B----%2B------------%2B
%7C0.5+%7Cs+++++++++++%7C
%7C0.2+%7Cs+++++++++++%7C
%7C1.0+%7Cn+++++++++++%7C
%7C4.0+%7Cn+++++++++++%7C
%2B----%2B------------%2B
*/|code-block|syntax|javascript|679090|entityMap|0|LINK|mutability|MUTABLE|url|https://stackoverflow.com/questions/44671597/how-to-replace-null-values-with-a-specific-value-in-dataframe-using-spark-in-jav|1|https://spark.apache.org/docs/2.1.0/api/java/index.html?org/apache/spark/sql/DataFrameNaFunctions.html^0|0|E|0|0|0|A|1|0|0|0^^$0|@$1|2|3|4|5|6|7|W|8|@]|9|@$A|X|B|Y|1|Z]]|C|$]]|$1|D|3|E|5|6|7|10|8|@]|9|@$A|11|B|12|1|13]]|C|$]]|$1|F|3|G|5|6|7|14|8|@]|9|@]|C|$]]|$1|H|3|I|5|J|7|15|8|@]|9|@]|C|$K|L]]|$1|M|3|-4|5|6|7|16|8|@]|9|@]|C|$]]]|N|$O|$5|P|Q|R|C|$S|T]]|U|$5|P|Q|R|C|$S|V]]]]

<a href="https://stackoverflow.com/questions/44671597/how-to-replace-null-values-with-a-specific-value-in-dataframe-using-spark-in-jav">DataFrame na fill</a>
<a href="https://spark.apache.org/docs/2.1.0/api/java/index.html?org/apache/spark/sql/DataFrameNaFunctions.html" rel="nofollow noreferrer">Class DataFrame</a>
for your question new value to every row
<pre><code>import org.apache.spark.sql.SparkSession
import org.apache.spark.sql.functions._
import spark.implicits._
val df1 = Seq((0.5f, &quot;v1&quot;), (0.2f, &quot;v2&quot;), (1f, &quot;v3&quot;), (4f, &quot;v4&quot;))
 .toDF(&quot;prob&quot;, &quot;column_field&quot;)
df1.show(false)
/*
+----+------------+
|prob|column_field|
+----+------------+
|0.5 |v1 |
|0.2 |v2 |
|1.0 |v3 |
|4.0 |v4 |
+----+------------+
*/
val resDF = df1.withColumn(
 &quot;column_field&quot;,
 when(col(&quot;prob&quot;) &lt;= 0.5f, &quot;s&quot;)
 .otherwise(&quot;n&quot;)
)

resDF.show(false)
/*
+----+------------+
|prob|column_field|
+----+------------+
|0.5 |s |
|0.2 |s |
|1.0 |n |
|4.0 |n |
+----+------------+
*/
</code></pre>

Alright so that seems easy but i couldnt find any solution or responses to it. I simply have a dataframe with a column full of nulls, and i just want to fill it with &quot;s&quot; or &quot;n&quot; randomly.
I tried this
`
<pre><code>df.foreach(f=&gt;{
 
 if(random)
 f.get(4) = &quot;s&quot;
 else{f.get(4) = &quot;n&quot;}
})
</code></pre>
`
But doesnt work, cause i think f is just a list, not the actual value
The pseudo would be something like that:
<pre><code>for(i=0;i&lt;max_rows;i++)
 if(prob&lt;.5)
 {df[i][&quot;column_field&quot;] == &quot;s&quot;}
 else
 {df[i][&quot;column_field&quot;] == &quot;n&quot;}
</code></pre>

Accesing fields of all the rows of a dataframe SPARK

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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好吧，那似乎很容易，但我找不到任何解决办法或对它的反应。我只是有一个包含满为空的列的dataframe，我只想随机地填充"s“或"n”。我试过了df.foreach(f=>{    if(random)    f.get(4) = "s"  else{f.get(4) = "n"}})`但是不起作用，因为我认为f只是一...

问访问数据火花的所有行的字段
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