Wow, thank you so much!
On Wed, Dec 21, 2022 at 10:27 AM Mich Talebzadeh <[email protected]>
wrote:
> OK let us try this
>
> 1) we have a csv file as below called cities.csv
>
> country,city,population
> Germany,Berlin,3520031
> Germany,Hamburg,1787408
> Germany,Munich,1450381
> Turkey,Ankara,4587558
> Turkey,Istanbul,14025646
> Turkey,Izmir,2847691
> United States,Chicago IL,2670406
> United States,Los Angeles CA,085014
> United States,New York City NY,8622357
>
> 2) Put this in HDFS as below
>
> hdfs dfs -put cities.csv /data/stg/test
>
> Read it into dataframe in PySpark as below
>
> csv_file="hdfs://rhes75:9000/data/stg/test/cities.csv"
> # read hive table in spark
> listing_df =
> spark.read.format("com.databricks.spark.csv").option("inferSchema",
> "true").option("header", "true").load(csv_file)
> listing_df.printSchema()
> print(f"""\n Reading from Hive table {csv_file}\n""")
> listing_df.show(100,False)
>
> 3) create spark temp table from the Dataframe. I call it temp
>
> print(f"""\n Reading from temp table temp created on listing_df\n""")
> listing_df.createOrReplaceTempView("temp")
>
> 4) use standard sql with windowing to get the result out
>
> sqltext = """
> SELECT country, city
> FROM
> (
> SELECT
> country AS country
> , city AS city
> , DENSE_RANK() OVER (PARTITION BY country ORDER BY population)
> AS RANK
> , max(population) OVER (PARTITION by country ORDER BY country,
> city) AS population
> FROM temp
> GROUP BY country, city, population
> )
> WHERE RANK in (3)
> ORDER by population DESC
> """
> spark.sql(sqltext).show()
>
> 4) let us test it
>
> root
> |-- country: string (nullable = true)
> |-- city: string (nullable = true)
> |-- population: double (nullable = true)
>
>
> Reading from Hive table hdfs://rhes75:9000/data/stg/test/cities.csv
>
> +-------------+----------------+-----------+
> |country |city |population |
> +-------------+----------------+-----------+
> |Germany |Berlin |3520031.0 |
> |Germany |Hamburg |1787408.0 |
> |Germany |Munich |1450381.0 |
> |Turkey |Ankara |4587558.0 |
> |Turkey |Istanbul |1.4025646E7|
> |Turkey |Izmir |2847691.0 |
> |United States|Chicago IL |2670406.0 |
> |United States|Los Angeles CA |85014.0 |
> |United States|New York City NY|8622357.0 |
> +-------------+----------------+-----------+
>
>
> Reading from temp table temp created on listing_df
>
> +-------------+----------------+
> | country| city|
> +-------------+----------------+
> | Turkey| Istanbul|
> |United States|New York City NY|
> | Germany| Berlin|
> +-------------+----------------+
>
> The codes are attached
>
> I am sure it can be improved.
>
>
>
> view my Linkedin profile
> <https://www.linkedin.com/in/mich-talebzadeh-ph-d-5205b2/>
>
>
> https://en.everybodywiki.com/Mich_Talebzadeh
>
>
>
> *Disclaimer:* Use it at your own risk. Any and all responsibility for any
> loss, damage or destruction of data or any other property which may arise
> from relying on this email's technical content is explicitly disclaimed.
> The author will in no case be liable for any monetary damages arising from
> such loss, damage or destruction.
>
>
>
>
> On Tue, 20 Dec 2022 at 20:35, Oliver Ruebenacker <
> [email protected]> wrote:
>
>>
>> Hello,
>>
>> Let's say the data is like this:
>>
>> +---------------+-------------------+------------+
>> | country | city | population |
>> +---------------+-------------------+------------+
>> | Germany | Berlin | 3520031 |
>> | Germany | Hamburg | 1787408 |
>> | Germany | Munich | 1450381 |
>> | Turkey | Ankara | 4587558 |
>> | Turkey | Istanbul | 14025646 |
>> | Turkey | Izmir | 2847691 |
>> | United States | Chicago, IL | 2670406 |
>> | United States | Los Angeles, CA | 4085014 |
>> | United States | New York City, NY | 8622357 |
>> +---------------+-------------------+------------+
>>
>> I want to get the largest city in each country:
>>
>> +---------------+-------------------+
>> | country | city |
>> +---------------+-------------------+
>> | Germany | Berlin |
>> | Turkey | Istanbul |
>> | United States | New York City, NY |
>> +---------------+-------------------+
>>
>> Thanks!
>>
>> Best, Oliver
>>
>> On Tue, Dec 20, 2022 at 5:52 AM Mich Talebzadeh <
>> [email protected]> wrote:
>>
>>> Hi,
>>>
>>> Windowing functions were invented to avoid doing lengthy group by etc.
>>>
>>> As usual there is a lot of heat but little light
>>>
>>> Please provide:
>>>
>>>
>>> 1. Sample input. I gather this data is stored in some csv, tsv,
>>> table format
>>> 2. The output that you would like to see.
>>>
>>>
>>> Have a look at this article of mine Technical Analysis of the latest
>>> UK House Price Index, Deploying Modern tools
>>> <https://www.linkedin.com/pulse/technical-analysis-latest-uk-house-price-index-modern-mich/>
>>>
>>>
>>> The PySpark code and windowing functions are here
>>> <https://github.com/michTalebzadeh/DataScience/blob/datascience/src/workoutYearlyAveragePricesAll.py>
>>>
>>>
>>> HTH
>>>
>>>
>>> view my Linkedin profile
>>> <https://www.linkedin.com/in/mich-talebzadeh-ph-d-5205b2/>
>>>
>>>
>>> https://en.everybodywiki.com/Mich_Talebzadeh
>>>
>>>
>>>
>>> *Disclaimer:* Use it at your own risk. Any and all responsibility for
>>> any loss, damage or destruction of data or any other property which may
>>> arise from relying on this email's technical content is explicitly
>>> disclaimed. The author will in no case be liable for any monetary damages
>>> arising from such loss, damage or destruction.
>>>
>>>
>>>
>>>
>>> On Mon, 19 Dec 2022 at 16:44, Oliver Ruebenacker <
>>> [email protected]> wrote:
>>>
>>>>
>>>> Hello,
>>>>
>>>> Thank you for the response!
>>>>
>>>> I can think of two ways to get the largest city by country, but both
>>>> seem to be inefficient:
>>>>
>>>> (1) I could group by country, sort each group by population, add the
>>>> row number within each group, and then retain only cities with a row number
>>>> equal to 1. But it seems wasteful to sort everything when I only want the
>>>> largest of each country
>>>>
>>>> (2) I could group by country, get the maximum city population for
>>>> each country, join that with the original data frame, and then retain only
>>>> cities with population equal to the maximum population in the country. But
>>>> that seems also expensive because I need to join.
>>>>
>>>> Am I missing something?
>>>>
>>>> Thanks!
>>>>
>>>> Best, Oliver
>>>>
>>>> On Mon, Dec 19, 2022 at 10:59 AM Mich Talebzadeh <
>>>> [email protected]> wrote:
>>>>
>>>>> In spark you can use windowing function
>>>>> <https://sparkbyexamples.com/spark/spark-sql-window-functions/>s to
>>>>> achieve this
>>>>>
>>>>> HTH
>>>>>
>>>>>
>>>>> view my Linkedin profile
>>>>> <https://www.linkedin.com/in/mich-talebzadeh-ph-d-5205b2/>
>>>>>
>>>>>
>>>>> https://en.everybodywiki.com/Mich_Talebzadeh
>>>>>
>>>>>
>>>>>
>>>>> *Disclaimer:* Use it at your own risk. Any and all responsibility for
>>>>> any loss, damage or destruction of data or any other property which may
>>>>> arise from relying on this email's technical content is explicitly
>>>>> disclaimed. The author will in no case be liable for any monetary damages
>>>>> arising from such loss, damage or destruction.
>>>>>
>>>>>
>>>>>
>>>>>
>>>>> On Mon, 19 Dec 2022 at 15:28, Oliver Ruebenacker <
>>>>> [email protected]> wrote:
>>>>>
>>>>>>
>>>>>> Hello,
>>>>>>
>>>>>> How can I retain from each group only the row for which one value
>>>>>> is the maximum of the group? For example, imagine a DataFrame containing
>>>>>> all major cities in the world, with three columns: (1) City name (2)
>>>>>> Country (3) population. How would I get a DataFrame that only contains
>>>>>> the
>>>>>> largest city in each country? Thanks!
>>>>>>
>>>>>> Best, Oliver
>>>>>>
>>>>>> --
>>>>>> Oliver Ruebenacker, Ph.D. (he)
>>>>>> Senior Software Engineer, Knowledge Portal Network
>>>>>> <http://kp4cd.org/>, Flannick Lab <http://www.flannicklab.org/>, Broad
>>>>>> Institute <http://www.broadinstitute.org/>
>>>>>>
>>>>>
>>>>
>>>> --
>>>> Oliver Ruebenacker, Ph.D. (he)
>>>> Senior Software Engineer, Knowledge Portal Network <http://kp4cd.org/>,
>>>> Flannick Lab <http://www.flannicklab.org/>, Broad Institute
>>>> <http://www.broadinstitute.org/>
>>>>
>>>
>>
>> --
>> Oliver Ruebenacker, Ph.D. (he)
>> Senior Software Engineer, Knowledge Portal Network <http://kp4cd.org/>,
>> Flannick
>> Lab <http://www.flannicklab.org/>, Broad Institute
>> <http://www.broadinstitute.org/>
>>
>
--
Oliver Ruebenacker, Ph.D. (he)
Senior Software Engineer, Knowledge Portal Network
<http://kp4cd.org/>, Flannick
Lab <http://www.flannicklab.org/>, Broad Institute
<http://www.broadinstitute.org/>
