Hi All,
I have tried the same result with pyspark and with SQL query by creating
with tempView, I could able to achieve whereas I have to do in the pyspark
code itself, Could you help on this
incoming_data = [["a"], ["b"], ["d"]]
column_names = ["column1"]
df =
Thanks Mich,
I have tried this solution, but i want all the columns from the dataframe
df_1, if i explode the df_1 i am getting only data column. But the
resultant should get the all the column from the df_1 with distinct result
like below.
Results in
*df:*
+---+
|column1|
+---+
|
You can use a combination of explode and distinct before joining.
from pyspark.sql import SparkSession
from pyspark.sql.functions import explode
# Create a SparkSession
spark = SparkSession.builder \
.appName("JoinExample") \
.getOrCreate()
sc = spark.sparkContext
# Set the log level to
Hi All,
Could anyone have any idea or suggestion of any alternate way to achieve
this scenario?
Thanks.
On Sat, May 11, 2024 at 6:55 AM Damien Hawes wrote:
> Right now, with the structure of your data, it isn't possible.
>
> The rows aren't duplicates of each other. "a" and "b" both exist in
Right now, with the structure of your data, it isn't possible.
The rows aren't duplicates of each other. "a" and "b" both exist in the
array. So Spark is correctly performing the join. It looks like you need to
find another way to model this data to get what you want to achieve.
Are the values
Hi Mich,
Thanks for the solution, But I am getting duplicate result by using
array_contains. I have explained the scenario below, could you help me on
that, how we can achieve i have tried different way bu i could able to
achieve.
For example
data = [
["a"],
["b"],
["d"],
]
This is what you want, how to join two DFs with a string column in one and
an array of strings in the other, keeping only rows where the string is
present in the array.
from pyspark.sql import SparkSession
from pyspark.sql import Row
from pyspark.sql.functions import expr
spark =
Hi All,
I have two dataframe with below structure, i have to join these two
dataframe - the scenario is one column is string in one dataframe and in
other df join column is array of string, so we have to inner join two df
and get the data if string value is present in any of the array of string
