Data from Azure sql server was read into databricks through JDBC connection (spark version 2.x) and stored into Gen1. Now the client wants to migrate the data from Gen1 to Gen2. When we ran the same jobs that read data from Azure Sql Server to Databr...
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We are trying to read a column which is enum of array datatype from postgres as string datatype to target. We could able to achieve this by expilcitly using concat function while extracting like belowval jdbcDF3 = spark.read .format("jdbc") .option(...
[DATATYPE_MISMATCH.BINARY_OP_DIFF_TYPES] Cannot resolve "(DocDate AND orderedhl)" due to data type mismatch: the left and right operands of the binary operator have incompatible types ("STRING" and "DECIMAL(38,6)").; line 67, pos 066. group by 67. or...
Hi,I'm trying to create a delta table using SQL but I'm getting this errorError in SQL statement: AnalysisException: cannot resolve '(CAST(10000 AS BIGINT) div Khe)' due to data type mismatch: differing types in '(CAST(10000 AS BIGINT) div Khe)' (big...
Hi @Adalberto Garcia Espinosa​ Do you need khe column to be double? If not, below query is working:%sql CREATE OR REPLACE TABLE Productos(Khe bigint NOT NULL,Fctor_HL_Estiba bigint GENERATED ALWAYS AS (cast(10000 as bigint) div Khe)) seems to be work...
select float('92233464567.33') returns 92,233,466,000I am expected result will be around 92,233,464,567.xxtherefore, float data type should be avoided.Use double or decimal works as expected. But I see float data type is widely used assuming most num...
Float is Approximate-number data type, which means that not all values in the data type range can be represented exactly.Decimal/Numeric is Fixed-Precision data type, which means that all the values in the data type range can be represented exactly w...
What I am doing:spark_df = spark.createDataFrame(dfnew)spark_df.write.saveAsTable("default.test_table", index=False, header=True)This automatically detects the datatypes and is working right now. BUT, what if the datatype cannot be detected or detect...
just create table earlier and set column types (CREATE TABLE ... LOCATION ( path path)in dataframe you need to have corresponding data types which you can make using cast syntax, just your syntax is incorrect, here is example of correct syntax:from p...
I'm relatively new to Scala. In the past, I was able to do the following python:
def foo(p1, p2):
import datetime as dt
dt.datetime(2014, 4, 17, 12, 34)
result = [
(1, "1", 1.1, dt.datetime(2014, 4, 17, 1, 0)),
(2, "2", 2...
Hello,
Just in case, here is an example for proposed solution above:
import org.apache.spark.sql.functions._
import org.apache.spark.sql.expressions._
import org.apache.spark.sql.types._
val data = Seq(("A", Seq((3,4),(5,6),(7,10))), ("B", Seq((-1,...
