Using 'as' in the 'WHERE' clause in spark sql
Date : March 29 2020, 07:55 AM
This might help you Is total a defined column in VIEW, or are you trying to filter on the value of count(*)? If you want to count and then filter on that count, the syntax should be something like: select <fieldtogroupon>, count(*) as total
from VIEW
group by <fieldtogroupon>
having count(*) > 1
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Which One is faster? Spark SQL with Where clause or Use of Filter in Dataframe after Spark SQL
Date : March 29 2020, 07:55 AM
Does that help Using explain method to see the physical plan is a good way to determine performance. For example, the Zeppelin Tutorial notebook. sqlContext.sql("select age, job from bank").filter("age = 30").explain
sqlContext.sql("select age, job from bank where age = 30").explain
== Physical Plan ==
Project [age#5,job#6]
+- Filter (age#5 = 30)
+- Scan ExistingRDD[age#5,job#6,marital#7,education#8,balance#9]
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Spark SQL between timestamp on where clause?
Date : March 29 2020, 07:55 AM
Does that help As you are using Timestamp in your where clause, you need to convert LocalDateTime to Timestamp. Also note that the first parameter of between is lowerBound so in your case LocalDateTime.now().minusHours(1) should come before LocalDateTime.now(). And then you can do: import java.time.LocalDateTime
import java.sql.Timestamp
df.where(
unix_timestamp($"date", "yyyy-MM-dd HH:mm:ss.S")
.cast("timestamp")
.between(
Timestamp.valueOf(LocalDateTime.now().minusHours(1)),
Timestamp.valueOf(LocalDateTime.now())
))
.show()
+-----+--------------------+
|color| date|
+-----+--------------------+
| red|2016-11-29 10:58:...|
+-----+--------------------+
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Does Spark Supports With Clause?
Date : March 29 2020, 07:55 AM
Does that help The WITH statement is not the problem, but rather the INSERT INTO statement that's causing trouble. Here's a working example that uses the .insertInto() style instead of the "INSERT INTO" SQL: val s = Seq((1,"foo"), (2, "bar"))
s: Seq[(Int, String)] = List((1,foo), (2,bar))
val df = s.toDF("id", "name")
df.registerTempTable("df")
sql("CREATE TABLE edf_final (id int, name string)")
val e = sql("WITH edf AS (SELECT id+1, name FROM df cook) SELECT * FROM edf")
e.insertInto("edf_final")
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How to use UDF in where clause in Scala Spark
Tag : scala , By : cthulhup
Date : March 29 2020, 07:55 AM
I hope this helps you . I'm trying to check if 2 Double columns are equal in a Dataframe to a certain degree of precision, so 49.999999 should equal 50. Is it possible to create a UDF and use it in a where clause? I am using Spark 2.0 in Scala. , You can use udf but there is no need for that: import org.apache.spark.sql.functions._
val precision: Double = ???
df.where(abs($"col1" - $"col2") < precision)
df.where(yourUdf($"col1", $"col2"))
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