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Posted to issues@spark.apache.org by "Bin Wu (JIRA)" <ji...@apache.org> on 2017/03/10 11:45:04 UTC

[jira] [Updated] (SPARK-19895) Spark SQL could not output a correct result

     [ https://issues.apache.org/jira/browse/SPARK-19895?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Bin Wu updated SPARK-19895:
---------------------------
    Description: 
I'm rewriting pagerank algorithm with Spark SQL, following is the code:

from pyspark.sql.functions import *
from pyspark.sql import SparkSession

spark = SparkSession \
        .builder \
        .appName("Python Spark SQL basic example") \
        .config("spark.some.config.option", "some-value") \
        .getOrCreate()

numOfIterations = 5                                                                             
lines = spark.read.text("pagerank_data.txt")

a = lines.select(split(lines[0],' '))
links = a.select(a[0][0].alias('src'), a[0][1].alias('dst'))
outdegrees = links.groupBy('src').count()
ranks = outdegrees.select('src', lit(1).alias('rank'))

for iteration in range(numOfIterations):
    contribs = links.join(ranks, 'src').join(outdegrees, 'src').select('dst', (ranks['rank']/outdegrees['count']).alias('contrib'))
    #ranks = contribs.groupBy('dst').sum('contrib').select(column('dst').alias('src'), (column('sum(contrib)')*0.85+0.15).alias('rank'))
    ranks = contribs.withColumnRenamed('dst','dst').groupBy('dst').sum('contrib').select(column('dst').alias('src'), (column('sum(contrib)')*0.85+0.15).alias('rank'))

ranks.orderBy(desc('rank')).show()

pagerank_data.txt only has several edges:
1 2
1 3
1 4
2 1
3 1
4 1

It cannot output correct rank for each node for this small graph only if I use the "withColumnRenamed". However, on large data set, the line without withColumnRenamed works correctly.

  was:
I'm rewriting pagerank algorithm with Spark SQL, following is the code:

from pyspark.sql.functions import *
from pyspark.sql import SparkSession

spark = SparkSession \
        .builder \
        .appName("Python Spark SQL basic example") \
        .config("spark.some.config.option", "some-value") \
        .getOrCreate()

numOfIterations = 5                                                                             
lines = spark.read.text("pagerank_data.txt")

a = lines.select(split(lines[0],' '))
links = a.select(a[0][0].alias('src'), a[0][1].alias('dst'))
outdegrees = links.groupBy('src').count()
ranks = outdegrees.select('src', lit(1).alias('rank'))

for iteration in range(numOfIterations):
    contribs = links.join(ranks, 'src').join(outdegrees, 'src').select('dst', (ranks['rank']/outdegrees['count']).alias('contrib'))
    #ranks = contribs.groupBy('dst').sum('contrib').select(column('dst').alias('src'), (column('sum(contrib)')*0.85+0.15).alias('rank'))
    ranks = contribs.withColumnRenamed('dst','dst').groupBy('dst').sum('contrib').select(column('dst').alias('src'), (column('sum(contrib)')*0.85+0.15).alias('rank'))

ranks.orderBy(desc('rank')).show()

pagerank_data.txt only have several edges:
1 2
1 3
1 4
2 1
3 1
4 1

It cannot output correct rank for each node for this small graph only if I use the "withColumnRenamed". However, on large data set, the line without withColumnRenamed works correctly.


> Spark SQL could not output a correct result
> -------------------------------------------
>
>                 Key: SPARK-19895
>                 URL: https://issues.apache.org/jira/browse/SPARK-19895
>             Project: Spark
>          Issue Type: Bug
>          Components: SQL
>    Affects Versions: 2.0.0, 2.1.0
>            Reporter: Bin Wu
>            Priority: Minor
>              Labels: beginner
>
> I'm rewriting pagerank algorithm with Spark SQL, following is the code:
> from pyspark.sql.functions import *
> from pyspark.sql import SparkSession
> spark = SparkSession \
>         .builder \
>         .appName("Python Spark SQL basic example") \
>         .config("spark.some.config.option", "some-value") \
>         .getOrCreate()
> numOfIterations = 5                                                                             
> lines = spark.read.text("pagerank_data.txt")
> a = lines.select(split(lines[0],' '))
> links = a.select(a[0][0].alias('src'), a[0][1].alias('dst'))
> outdegrees = links.groupBy('src').count()
> ranks = outdegrees.select('src', lit(1).alias('rank'))
> for iteration in range(numOfIterations):
>     contribs = links.join(ranks, 'src').join(outdegrees, 'src').select('dst', (ranks['rank']/outdegrees['count']).alias('contrib'))
>     #ranks = contribs.groupBy('dst').sum('contrib').select(column('dst').alias('src'), (column('sum(contrib)')*0.85+0.15).alias('rank'))
>     ranks = contribs.withColumnRenamed('dst','dst').groupBy('dst').sum('contrib').select(column('dst').alias('src'), (column('sum(contrib)')*0.85+0.15).alias('rank'))
> ranks.orderBy(desc('rank')).show()
> pagerank_data.txt only has several edges:
> 1 2
> 1 3
> 1 4
> 2 1
> 3 1
> 4 1
> It cannot output correct rank for each node for this small graph only if I use the "withColumnRenamed". However, on large data set, the line without withColumnRenamed works correctly.



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