Mixing
partitioning data in rdd and saving partitioned chunks
Hi I've following rdd :
Header :
id|category|date|name|age
contents of rdd
1|b|12-10-2015|David|20
2|c|12-10-2015|Moses|40
3|b|18-12-2016|Tom|30
4|c|18-12-2016|Bill|60
I want to partition the data by category and date and save the files as follows :
12102015_b
1|b|12-10-2015|David|20
12102015_c
2|c|12-10-2015|Moses|40
18122016_b
3|b|18-12-2016|Tom|30
18122016_c
4|c|18-12-2016|Bill|60
Can I get any suggestions for this. Thanks in advance!!!
python apache-spark pyspark rdd
asked Nov 19 '18 at 12:26
Avinash Clinton
1739
add a comment |
Hi I've following rdd :
Header :
id|category|date|name|age
contents of rdd
1|b|12-10-2015|David|20
2|c|12-10-2015|Moses|40
3|b|18-12-2016|Tom|30
4|c|18-12-2016|Bill|60
I want to partition the data by category and date and save the files as follows :
12102015_b
1|b|12-10-2015|David|20
12102015_c
2|c|12-10-2015|Moses|40
18122016_b
3|b|18-12-2016|Tom|30
18122016_c
4|c|18-12-2016|Bill|60
Can I get any suggestions for this. Thanks in advance!!!
python apache-spark pyspark rdd
asked Nov 19 '18 at 12:26
Avinash Clinton
1739
add a comment |
Hi I've following rdd :
Header :
id|category|date|name|age
contents of rdd
1|b|12-10-2015|David|20
2|c|12-10-2015|Moses|40
3|b|18-12-2016|Tom|30
4|c|18-12-2016|Bill|60
I want to partition the data by category and date and save the files as follows :
12102015_b
1|b|12-10-2015|David|20
12102015_c
2|c|12-10-2015|Moses|40
18122016_b
3|b|18-12-2016|Tom|30
18122016_c
4|c|18-12-2016|Bill|60
Can I get any suggestions for this. Thanks in advance!!!
python apache-spark pyspark rdd
asked Nov 19 '18 at 12:26
Avinash Clinton
1739
Hi I've following rdd :
Header :
id|category|date|name|age
contents of rdd
1|b|12-10-2015|David|20
2|c|12-10-2015|Moses|40
3|b|18-12-2016|Tom|30
4|c|18-12-2016|Bill|60
I want to partition the data by category and date and save the files as follows :
12102015_b
1|b|12-10-2015|David|20
12102015_c
2|c|12-10-2015|Moses|40
18122016_b
3|b|18-12-2016|Tom|30
18122016_c
4|c|18-12-2016|Bill|60
Can I get any suggestions for this. Thanks in advance!!!
python apache-spark pyspark rdd
python apache-spark pyspark rdd
asked Nov 19 '18 at 12:26
Avinash Clinton
1739
asked Nov 19 '18 at 12:26
Avinash Clinton
1739
asked Nov 19 '18 at 12:26
Avinash Clinton
1739
asked Nov 19 '18 at 12:26
Avinash Clinton
1739
asked Nov 19 '18 at 12:26
Avinash Clinton
1739
1739
add a comment |
add a comment |
1 Answer
1
active
oldest
votes
Suppose you have all your above data in pyspark dataframe df.
Then you can use below statement to partition the data based on date and then category (however, you can decide the order based on your business logic.) and then save the dataFrame in various different format. However, I am using csv in below example.
df.write.partitionBy("date", "category").csv("location_of_path")
You can find a reference here for csv, parquet, partitionBy.
Hope this helps.
Regards,
Neeraj
answered Nov 19 '18 at 14:19
neeraj bhadani
739211
add a comment |
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1 Answer
1
active
oldest
votes
1 Answer
1
active
oldest
votes
active
oldest
votes
active
oldest
votes
Suppose you have all your above data in pyspark dataframe df.
Then you can use below statement to partition the data based on date and then category (however, you can decide the order based on your business logic.) and then save the dataFrame in various different format. However, I am using csv in below example.
df.write.partitionBy("date", "category").csv("location_of_path")
You can find a reference here for csv, parquet, partitionBy.
Hope this helps.
Regards,
Neeraj
answered Nov 19 '18 at 14:19
neeraj bhadani
739211
add a comment |
Suppose you have all your above data in pyspark dataframe df.
Then you can use below statement to partition the data based on date and then category (however, you can decide the order based on your business logic.) and then save the dataFrame in various different format. However, I am using csv in below example.
df.write.partitionBy("date", "category").csv("location_of_path")
You can find a reference here for csv, parquet, partitionBy.
Hope this helps.
Regards,
Neeraj
answered Nov 19 '18 at 14:19
neeraj bhadani
739211
add a comment |
Suppose you have all your above data in pyspark dataframe df.
Then you can use below statement to partition the data based on date and then category (however, you can decide the order based on your business logic.) and then save the dataFrame in various different format. However, I am using csv in below example.
df.write.partitionBy("date", "category").csv("location_of_path")
You can find a reference here for csv, parquet, partitionBy.
Hope this helps.
Regards,
Neeraj
answered Nov 19 '18 at 14:19
neeraj bhadani
739211
Suppose you have all your above data in pyspark dataframe df.
Then you can use below statement to partition the data based on date and then category (however, you can decide the order based on your business logic.) and then save the dataFrame in various different format. However, I am using csv in below example.
df.write.partitionBy("date", "category").csv("location_of_path")
You can find a reference here for csv, parquet, partitionBy.
Hope this helps.
Regards,
Neeraj
answered Nov 19 '18 at 14:19
neeraj bhadani
739211
answered Nov 19 '18 at 14:19
neeraj bhadani
739211
answered Nov 19 '18 at 14:19
neeraj bhadani
739211
answered Nov 19 '18 at 14:19
neeraj bhadani
739211
739211
add a comment |
add a comment |
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