blocks|key|663851|text|Either使用|type|unstyled|depth|inlineStyleRanges|entityRanges|offset|length|data|663852|663853|数据集选择(字符串col，scala.collection.Seq+cols)|blockquote|663854|663855|663856|作为|663857|Column+column+=+"col1";
List<String>+columns+=+Arrays.toList(""col2","col3");
ds.select(column,+columns).show()|code-block|syntax|javascript|663858|or|663859|663860|数据集选择(字符串列，字符串...cols)|663861|663862|663863|663864|List<Column>+columns+=+Arrays.toList(col("col1"),col("col2"),col("col3"));
ds.select(columns);|663865|entityMap|0|LINK|mutability|MUTABLE|url|https://spark.apache.org/docs/latest/api/java/org/apache/spark/sql/Dataset.html#select-java.lang.String-scala.collection.Seq-|1|https://spark.apache.org/docs/latest/api/java/org/apache/spark/sql/Dataset.html#select-scala.collection.Seq-^0|0|6|0|0|0|0|0|0|0|0|0|2|1|0|0|0|0|0|0|0^^$0|@$1|2|3|4|5|6|7|1A|8|@]|9|@$A|1B|B|1C|1|1D]]|C|$]]|$1|D|3|-4|5|6|7|1E|8|@]|9|@]|C|$]]|$1|E|3|F|5|G|7|1F|8|@]|9|@]|C|$]]|$1|H|3|-4|5|6|7|1G|8|@]|9|@]|C|$]]|$1|I|3|-4|5|6|7|1H|8|@]|9|@]|C|$]]|$1|J|3|K|5|6|7|1I|8|@]|9|@]|C|$]]|$1|L|3|M|5|N|7|1J|8|@]|9|@]|C|$O|P]]|$1|Q|3|R|5|6|7|1K|8|@]|9|@$A|1L|B|1M|1|1N]]|C|$]]|$1|S|3|-4|5|6|7|1O|8|@]|9|@]|C|$]]|$1|T|3|U|5|G|7|1P|8|@]|9|@]|C|$]]|$1|V|3|-4|5|6|7|1Q|8|@]|9|@]|C|$]]|$1|W|3|-4|5|6|7|1R|8|@]|9|@]|C|$]]|$1|X|3|K|5|6|7|1S|8|@]|9|@]|C|$]]|$1|Y|3|Z|5|N|7|1T|8|@]|9|@]|C|$O|P]]|$1|10|3|-4|5|6|7|1U|8|@]|9|@]|C|$]]]|11|$12|$5|13|14|15|C|$16|17]]|18|$5|13|14|15|C|$16|19]]]]

<a href="https://spark.apache.org/docs/latest/api/java/org/apache/spark/sql/Dataset.html#select-java.lang.String-scala.collection.Seq-" rel="nofollow noreferrer">Either</a> use

<blockquote>
<pre><code>Dataset&lt;Row&gt; select(String col, scala.collection.Seq&lt;String&gt; cols)
</code></pre>
</blockquote>

as

<pre><code>Column column = "col1";
List&lt;String&gt; columns = Arrays.toList(""col2","col3");
ds.select(column, columns).show()
</code></pre>

<a href="https://spark.apache.org/docs/latest/api/java/org/apache/spark/sql/Dataset.html#select-scala.collection.Seq-" rel="nofollow noreferrer">or</a>

<blockquote>
<pre><code> Dataset&lt;Row&gt; select(String col, String... cols)
</code></pre>
</blockquote>

as

<pre><code>List&lt;Column&gt; columns = Arrays.toList(col("col1"),col("col2"),col("col3"));
ds.select(columns);
</code></pre>

blocks|key|859382|text|使用spark+2.4.0时，您必须将List<String>转换为Seq<String>，并按照spark文档使用selectExpr。|type|unstyled|depth|inlineStyleRanges|offset|length|style|CODE|entityRanges|data|859383|如果要使用select，则必须从列表中删除第一列，并将其作为参数添加到select中。|859384|请找到两个版本：|859385|假设您有以下.csv文件：|859386|InvoiceNo,StockCode,Description,Quantity,InvoiceDate,UnitPrice,CustomerID,Country
536365,85123A,WHITE+HANGING+HEART+T-LIGHT+HOLDER,6,2010-12-01+08:26:00,2.55,17850.0,United+Kingdom
536365,71053,WHITE+METAL+LANTERN,6,2010-12-01+08:26:00,3.39,17850.0,United+Kingdom
536365,84406B,CREAM+CUPID+HEARTS+COAT+HANGER,8,2010-12-01+08:26:00,2.75,17850.0,United+Kingdom
536365,84029G,KNITTED+UNION+FLAG+HOT+WATER+BOTTLE,6,2010-12-01+08:26:00,3.39,17850.0,United+Kingdom
536365,84029E,RED+WOOLLY+HOTTIE+WHITE+HEART.,6,2010-12-01+08:26:00,3.39,17850.0,United+Kingdom|code-block|syntax|javascript|859387|您可以使用以下代码来解决您的问题：|859388|import+org.apache.spark.sql.Dataset;
import+org.apache.spark.sql.Row;
import+org.apache.spark.sql.SparkSession;

import+java.util.Arrays;
import+java.util.List;
import+scala.collection.JavaConverters;
import+scala.collection.Seq;


public+class+SparkJavaTest+{
++++public+static+SparkSession+spark+=+SparkSession
++++++++++++.builder()
++++++++++++.appName("JavaSparkTest")
++++++++++++.master("local")
++++++++++++.getOrCreate();

++++public+static+Seq<String>+convertListToSeq(List<String>+inputList)+{
++++++++return+JavaConverters.asScalaIteratorConverter(inputList.iterator()).asScala().toSeq();
++++}

++++public+static+void+main(String[]+args)+{
++++++++Dataset<Row>+ds+=+spark.read().option("header",true).csv("spark-file.csv");

++++++++List<String>+columns+=+Arrays.asList("InvoiceNo","StockCode","Description");

++++++++//using+selectExpr
++++++++ds.selectExpr(convertListToSeq(columns)).show(false);

++++++++//using+select+=>+this+first+column+will+be+added+to+select
++++++++List<String>+columns2+=+Arrays.asList("StockCode","Description");

++++++++ds.select("InvoiceNo",+convertListToSeq(columns2)).show(false);

++++}
}|859389|希望它能有所帮助:)|859390|entityMap^0|2|B|J|C|Y|B|1M|A|0|5|6|Z|6|0|0|6|4|0|0|0|0|0^^$0|@$1|2|3|4|5|6|7|Y|8|@$9|Z|A|10|B|C]|$9|11|A|12|B|C]|$9|13|A|14|B|C]|$9|15|A|16|B|C]]|D|@]|E|$]]|$1|F|3|G|5|6|7|17|8|@$9|18|A|19|B|C]|$9|1A|A|1B|B|C]]|D|@]|E|$]]|$1|H|3|I|5|6|7|1C|8|@]|D|@]|E|$]]|$1|J|3|K|5|6|7|1D|8|@$9|1E|A|1F|B|C]]|D|@]|E|$]]|$1|L|3|M|5|N|7|1G|8|@]|D|@]|E|$O|P]]|$1|Q|3|R|5|6|7|1H|8|@]|D|@]|E|$]]|$1|S|3|T|5|N|7|1I|8|@]|D|@]|E|$O|P]]|$1|U|3|V|5|6|7|1J|8|@]|D|@]|E|$]]|$1|W|3|-4|5|6|7|1K|8|@]|D|@]|E|$]]]|X|$]]

Using <code>spark 2.4.0</code> you have to convert the <code>List&lt;String&gt;</code> to <code>Seq&lt;String&gt;</code>, and use <code>selectExpr</code> following spark documentation.

If you want to use <code>select</code>, you have to remove the first column from your list and add it as a parameter to <code>select</code>. 

Please find the two versions : 

Suppose that you have the following <code>.csv</code> file : 

<pre><code>InvoiceNo,StockCode,Description,Quantity,InvoiceDate,UnitPrice,CustomerID,Country
536365,85123A,WHITE HANGING HEART T-LIGHT HOLDER,6,2010-12-01 08:26:00,2.55,17850.0,United Kingdom
536365,71053,WHITE METAL LANTERN,6,2010-12-01 08:26:00,3.39,17850.0,United Kingdom
536365,84406B,CREAM CUPID HEARTS COAT HANGER,8,2010-12-01 08:26:00,2.75,17850.0,United Kingdom
536365,84029G,KNITTED UNION FLAG HOT WATER BOTTLE,6,2010-12-01 08:26:00,3.39,17850.0,United Kingdom
536365,84029E,RED WOOLLY HOTTIE WHITE HEART.,6,2010-12-01 08:26:00,3.39,17850.0,United Kingdom
</code></pre>

You can use this code to solve your issue:

<pre><code>import org.apache.spark.sql.Dataset;
import org.apache.spark.sql.Row;
import org.apache.spark.sql.SparkSession;

import java.util.Arrays;
import java.util.List;
import scala.collection.JavaConverters;
import scala.collection.Seq;


public class SparkJavaTest {
 public static SparkSession spark = SparkSession
 .builder()
 .appName("JavaSparkTest")
 .master("local")
 .getOrCreate();

 public static Seq&lt;String&gt; convertListToSeq(List&lt;String&gt; inputList) {
 return JavaConverters.asScalaIteratorConverter(inputList.iterator()).asScala().toSeq();
 }

 public static void main(String[] args) {
 Dataset&lt;Row&gt; ds = spark.read().option("header",true).csv("spark-file.csv");

 List&lt;String&gt; columns = Arrays.asList("InvoiceNo","StockCode","Description");

 //using selectExpr
 ds.selectExpr(convertListToSeq(columns)).show(false);

 //using select =&gt; this first column will be added to select
 List&lt;String&gt; columns2 = Arrays.asList("StockCode","Description");

 ds.select("InvoiceNo", convertListToSeq(columns2)).show(false);

 }
}
</code></pre>

Hope it helps :)

How can I select multiple columns of dataset <code>ds</code> in Spark 2.3 Java by passing a list argument?

For example, this works fine:

<pre><code>ds.select("col1","col2","col3").show();
</code></pre>

However, this fails:

<pre><code>List&lt;String&gt; columns = Arrays.toList("col1","col2","col3");
ds.select(columns.toString()).show()
</code></pre>

How to select multiple columns of dataset, given a list of column names?

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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如何在Spark 2.3Java中通过传递列表参数来选择dataset ds的多列？例如，这可以很好地工作：ds.select("col1","col2","col3").show();但是，这会失败：List<String> columns = Arrays.toList("col1","col2","col3");...

问如何在给定列名列表的情况下选择数据集的多列？
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问如何在给定列名列表的情况下选择数据集的多列？EN