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Data Engineering
Join discussions on data engineering best practices, architectures, and optimization strategies within the Databricks Community. Exchange insights and solutions with fellow data engineers.
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Forum Posts

WenLin
by New Contributor II
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data.write.format('com.databricks.spark.csv') added additional quotation marks

0favorite I am using the following code (pyspark) to export my data frame to csv: data.write.format('com.databricks.spark.csv').options(delimiter="\t", codec="org.apache.hadoop.io.compress.GzipCodec").save('s3a://myBucket/myPath') Note that I use d...

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chaotic3quilibr
New Contributor III
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The way to turn off the default escaping of the double quote character (") with the backslash character (\) - i.e. to avoid escaping for all characters entirely, you must add an .option() method call with just the right parameters after the .write() ...

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SohelKhan
by New Contributor II
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Resolved! Pyspark DataFrame: Converting one column from string to float/double

Pyspark 1.6: DataFrame: Converting one column from string to float/double I have two columns in a dataframe both of which are loaded as string. DF = rawdata.select('house name', 'price') I want to convert DF.price to float. DF = rawdata.select('hous...

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AidanCondron
New Contributor II
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Slightly simpler: df_num = df.select(df.employment.cast("float"), df.education.cast("float"), df.health.cast("float")) This works with multiple columns, three shown here.

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dshosseinyousef
by New Contributor II
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how to Calculate quantile on grouped data in spark Dataframe

I have the following sparkdataframe : agent_id/ payment_amount a /1000 b /1100 a /1100 a /1200 b /1200 b /1250 a /10000 b /9000 my desire output would be something like <code>agen_id 95_quantile a whatever is95 quantile for a...

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Weiluo__David_R
New Contributor II
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For those of you who haven't run into this SO thread http://stackoverflow.com/questions/39633614/calculate-quantile-on-grouped-data-in-spark-dataframe, it's pointed out there that one work-around is to use HIVE UDF "percentile_approx". Please see th...

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dshosseinyousef
by New Contributor II
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How to extract year and week number from a columns in a sparkDataFrame?

I have the following sparkdataframe : sale_id/ created_at 1 /2016-05-28T05:53:31.042Z 2 /2016-05-30T12:50:58.184Z 3/ 2016-05-23T10:22:18.858Z 4 /2016-05-27T09:20:15.158Z 5 /2016-05-21T08:30:17.337Z 6 /2016-05-28T07:41:14.361Z i need t add a year-wee...

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theodondre
New Contributor II
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THIS IS HOW HE DOCUMENTATION LOOKS LIKE

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washim
by New Contributor III
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washim
New Contributor III
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got it use - features = dataset.map(lambda row: row[0:]) from pyspark.mllib.stat import Statistics corr_mat=Statistics.corr(features, method="pearson")

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Gabriela_DeQuer
by New Contributor
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rlgarris
Databricks Employee
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There is no hardcoded limit we just call panda.fromRecords with a collection of fields to instantiate a new Panda Dataframe. The only limit is memory. See http://stackoverflow.com/questions/15455722/pandas-is-there-a-max-size-max-no-of-columns-max-r...

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