Nested Structure traversal in Spark
How does spark resolve the field reference in a nested datastructure. For Example;
Following is a schema for a parquet file.
Data schema format
root
|
--- id
--- name
--- address
|
---street-name
---city
---state
---country
---hiredate
---designation
To query country field, I could use the following code in spark (scala).
The data is stored in a parquet file. The usecase (query) is to select all the employees who are not from country = "Somalia"
Using spark I'm able to achieve this as
val df = spark.read.parquet("filepath")
df.filter("address.country <> 'Somalia'").show()
How does spark resolve the "." (dot) to be a delimiter between child and parent in the nested structure and fetch the results. I'm looking for the part in spark source code which performs the task?. Appreciate any help.
I'm currently trying to use the same functionality in a mapreduce job to get the field but would need to traverse the structure.
apache-spark
asked Nov 27 '18 at 23:22
venBigDatavenBigData
319415
add a comment |
How does spark resolve the field reference in a nested datastructure. For Example;
Following is a schema for a parquet file.
Data schema format
root
|
--- id
--- name
--- address
|
---street-name
---city
---state
---country
---hiredate
---designation
To query country field, I could use the following code in spark (scala).
The data is stored in a parquet file. The usecase (query) is to select all the employees who are not from country = "Somalia"
Using spark I'm able to achieve this as
val df = spark.read.parquet("filepath")
df.filter("address.country <> 'Somalia'").show()
How does spark resolve the "." (dot) to be a delimiter between child and parent in the nested structure and fetch the results. I'm looking for the part in spark source code which performs the task?. Appreciate any help.
I'm currently trying to use the same functionality in a mapreduce job to get the field but would need to traverse the structure.
apache-spark
asked Nov 27 '18 at 23:22
venBigDatavenBigData
319415
add a comment |
How does spark resolve the field reference in a nested datastructure. For Example;
Following is a schema for a parquet file.
Data schema format
root
|
--- id
--- name
--- address
|
---street-name
---city
---state
---country
---hiredate
---designation
To query country field, I could use the following code in spark (scala).
The data is stored in a parquet file. The usecase (query) is to select all the employees who are not from country = "Somalia"
Using spark I'm able to achieve this as
val df = spark.read.parquet("filepath")
df.filter("address.country <> 'Somalia'").show()
How does spark resolve the "." (dot) to be a delimiter between child and parent in the nested structure and fetch the results. I'm looking for the part in spark source code which performs the task?. Appreciate any help.
I'm currently trying to use the same functionality in a mapreduce job to get the field but would need to traverse the structure.
apache-spark
asked Nov 27 '18 at 23:22
venBigDatavenBigData
319415
How does spark resolve the field reference in a nested datastructure. For Example;
Following is a schema for a parquet file.
Data schema format
root
|
--- id
--- name
--- address
|
---street-name
---city
---state
---country
---hiredate
---designation
To query country field, I could use the following code in spark (scala).
The data is stored in a parquet file. The usecase (query) is to select all the employees who are not from country = "Somalia"
Using spark I'm able to achieve this as
val df = spark.read.parquet("filepath")
df.filter("address.country <> 'Somalia'").show()
How does spark resolve the "." (dot) to be a delimiter between child and parent in the nested structure and fetch the results. I'm looking for the part in spark source code which performs the task?. Appreciate any help.
I'm currently trying to use the same functionality in a mapreduce job to get the field but would need to traverse the structure.
apache-spark
apache-spark
asked Nov 27 '18 at 23:22
venBigDatavenBigData
319415
asked Nov 27 '18 at 23:22
venBigDatavenBigData
319415
asked Nov 27 '18 at 23:22
venBigDatavenBigData
319415
asked Nov 27 '18 at 23:22
venBigDatavenBigData
319415
asked Nov 27 '18 at 23:22
venBigDatavenBigData
319415
319415
add a comment |
add a comment |
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