Mixing
Apache Spark to_json options parameter
I either don't know what I'm looking for or the documentation is lacking. The latter seems to be the case, given this:
http://spark.apache.org/docs/2.2.2/api/java/org/apache/spark/sql/functions.html#to_json-org.apache.spark.sql.Column-java.util.Map-
"options - options to control how the struct column is converted into a json string. accepts the same options and the json data source."
Great! So, what are my options?
I'm doing something like this:
Dataset<Row> formattedReader = reader
.withColumn("id", lit(id))
.withColumn("timestamp", lit(timestamp))
.withColumn("data", to_json(struct("record_count")));
...and I get this result:
{
"id": "ABC123",
"timestamp": "2018-11-16 20:40:26.108",
"data": "{"record_count": 989}"
}
I'd like this (remove back-slashes and quotes from "data"):
{
"id": "ABC123",
"timestamp": "2018-11-16 20:40:26.108",
"data": {"record_count": 989}
}
Is this one of the options by chance? Is there a better guide out there for Spark? The most frustrating part about Spark hasn't been getting it to do what I want, it's been a lack of good information on what it can do.
java json apache-spark dataframe apache-spark-sql
asked Nov 20 '18 at 0:26
Tsar BombaTsar Bomba
5322930
add a comment |
I either don't know what I'm looking for or the documentation is lacking. The latter seems to be the case, given this:
http://spark.apache.org/docs/2.2.2/api/java/org/apache/spark/sql/functions.html#to_json-org.apache.spark.sql.Column-java.util.Map-
"options - options to control how the struct column is converted into a json string. accepts the same options and the json data source."
Great! So, what are my options?
I'm doing something like this:
Dataset<Row> formattedReader = reader
.withColumn("id", lit(id))
.withColumn("timestamp", lit(timestamp))
.withColumn("data", to_json(struct("record_count")));
...and I get this result:
{
"id": "ABC123",
"timestamp": "2018-11-16 20:40:26.108",
"data": "{"record_count": 989}"
}
I'd like this (remove back-slashes and quotes from "data"):
{
"id": "ABC123",
"timestamp": "2018-11-16 20:40:26.108",
"data": {"record_count": 989}
}
Is this one of the options by chance? Is there a better guide out there for Spark? The most frustrating part about Spark hasn't been getting it to do what I want, it's been a lack of good information on what it can do.
java json apache-spark dataframe apache-spark-sql
asked Nov 20 '18 at 0:26
Tsar BombaTsar Bomba
5322930
You should parse JSON string first, only after that, applyto_json.
– user10465355
Nov 20 '18 at 0:38
add a comment |
I either don't know what I'm looking for or the documentation is lacking. The latter seems to be the case, given this:
http://spark.apache.org/docs/2.2.2/api/java/org/apache/spark/sql/functions.html#to_json-org.apache.spark.sql.Column-java.util.Map-
"options - options to control how the struct column is converted into a json string. accepts the same options and the json data source."
Great! So, what are my options?
I'm doing something like this:
Dataset<Row> formattedReader = reader
.withColumn("id", lit(id))
.withColumn("timestamp", lit(timestamp))
.withColumn("data", to_json(struct("record_count")));
...and I get this result:
{
"id": "ABC123",
"timestamp": "2018-11-16 20:40:26.108",
"data": "{"record_count": 989}"
}
I'd like this (remove back-slashes and quotes from "data"):
{
"id": "ABC123",
"timestamp": "2018-11-16 20:40:26.108",
"data": {"record_count": 989}
}
Is this one of the options by chance? Is there a better guide out there for Spark? The most frustrating part about Spark hasn't been getting it to do what I want, it's been a lack of good information on what it can do.
java json apache-spark dataframe apache-spark-sql
asked Nov 20 '18 at 0:26
Tsar BombaTsar Bomba
5322930
I either don't know what I'm looking for or the documentation is lacking. The latter seems to be the case, given this:
http://spark.apache.org/docs/2.2.2/api/java/org/apache/spark/sql/functions.html#to_json-org.apache.spark.sql.Column-java.util.Map-
"options - options to control how the struct column is converted into a json string. accepts the same options and the json data source."
Great! So, what are my options?
I'm doing something like this:
Dataset<Row> formattedReader = reader
.withColumn("id", lit(id))
.withColumn("timestamp", lit(timestamp))
.withColumn("data", to_json(struct("record_count")));
...and I get this result:
{
"id": "ABC123",
"timestamp": "2018-11-16 20:40:26.108",
"data": "{"record_count": 989}"
}
I'd like this (remove back-slashes and quotes from "data"):
{
"id": "ABC123",
"timestamp": "2018-11-16 20:40:26.108",
"data": {"record_count": 989}
}
Is this one of the options by chance? Is there a better guide out there for Spark? The most frustrating part about Spark hasn't been getting it to do what I want, it's been a lack of good information on what it can do.
java json apache-spark dataframe apache-spark-sql
java json apache-spark dataframe apache-spark-sql
asked Nov 20 '18 at 0:26
Tsar BombaTsar Bomba
5322930
asked Nov 20 '18 at 0:26
Tsar BombaTsar Bomba
5322930
asked Nov 20 '18 at 0:26
Tsar BombaTsar Bomba
5322930
asked Nov 20 '18 at 0:26
Tsar BombaTsar Bomba
5322930
asked Nov 20 '18 at 0:26
Tsar BombaTsar Bomba
5322930
5322930
You should parse JSON string first, only after that, applyto_json.
– user10465355
Nov 20 '18 at 0:38
add a comment |
You should parse JSON string first, only after that, applyto_json.
– user10465355
Nov 20 '18 at 0:38
You should parse JSON string first, only after that, apply
to_json.– user10465355
Nov 20 '18 at 0:38
You should parse JSON string first, only after that, apply
to_json.– user10465355
Nov 20 '18 at 0:38
add a comment |
1 Answer
1
active
oldest
votes
You are json encoding twice for the record_count field. Remove to_json. struct alone should be sufficient.
As in change your code to something like this.
Dataset<Row> formattedReader = reader
.withColumn("id", lit(id))
.withColumn("timestamp", lit(timestamp))
.withColumn("data", struct("record_count"));
answered Nov 20 '18 at 6:04
BiswanathBiswanath
5,009103856
Ha! I swear I had tried that and gotten an exception. It works. Thanks!
– Tsar Bomba
Nov 20 '18 at 15:43
Welcome ! It happens to best.
– Biswanath
Nov 20 '18 at 15:59
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
You are json encoding twice for the record_count field. Remove to_json. struct alone should be sufficient.
As in change your code to something like this.
Dataset<Row> formattedReader = reader
.withColumn("id", lit(id))
.withColumn("timestamp", lit(timestamp))
.withColumn("data", struct("record_count"));
answered Nov 20 '18 at 6:04
BiswanathBiswanath
5,009103856
Ha! I swear I had tried that and gotten an exception. It works. Thanks!
– Tsar Bomba
Nov 20 '18 at 15:43
Welcome ! It happens to best.
– Biswanath
Nov 20 '18 at 15:59
add a comment |
You are json encoding twice for the record_count field. Remove to_json. struct alone should be sufficient.
As in change your code to something like this.
Dataset<Row> formattedReader = reader
.withColumn("id", lit(id))
.withColumn("timestamp", lit(timestamp))
.withColumn("data", struct("record_count"));
answered Nov 20 '18 at 6:04
BiswanathBiswanath
5,009103856
Ha! I swear I had tried that and gotten an exception. It works. Thanks!
– Tsar Bomba
Nov 20 '18 at 15:43
Welcome ! It happens to best.
– Biswanath
Nov 20 '18 at 15:59
add a comment |
You are json encoding twice for the record_count field. Remove to_json. struct alone should be sufficient.
As in change your code to something like this.
Dataset<Row> formattedReader = reader
.withColumn("id", lit(id))
.withColumn("timestamp", lit(timestamp))
.withColumn("data", struct("record_count"));
answered Nov 20 '18 at 6:04
BiswanathBiswanath
5,009103856
You are json encoding twice for the record_count field. Remove to_json. struct alone should be sufficient.
As in change your code to something like this.
Dataset<Row> formattedReader = reader
.withColumn("id", lit(id))
.withColumn("timestamp", lit(timestamp))
.withColumn("data", struct("record_count"));
answered Nov 20 '18 at 6:04
BiswanathBiswanath
5,009103856
answered Nov 20 '18 at 6:04
BiswanathBiswanath
5,009103856
answered Nov 20 '18 at 6:04
BiswanathBiswanath
5,009103856
answered Nov 20 '18 at 6:04
BiswanathBiswanath
5,009103856
5,009103856
Ha! I swear I had tried that and gotten an exception. It works. Thanks!
– Tsar Bomba
Nov 20 '18 at 15:43
Welcome ! It happens to best.
– Biswanath
Nov 20 '18 at 15:59
add a comment |
Ha! I swear I had tried that and gotten an exception. It works. Thanks!
– Tsar Bomba
Nov 20 '18 at 15:43
Welcome ! It happens to best.
– Biswanath
Nov 20 '18 at 15:59
Ha! I swear I had tried that and gotten an exception. It works. Thanks!
– Tsar Bomba
Nov 20 '18 at 15:43
Ha! I swear I had tried that and gotten an exception. It works. Thanks!
– Tsar Bomba
Nov 20 '18 at 15:43
Welcome ! It happens to best.
– Biswanath
Nov 20 '18 at 15:59
Welcome ! It happens to best.
– Biswanath
Nov 20 '18 at 15:59
add a comment |
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You should parse JSON string first, only after that, apply
to_json.– user10465355
Nov 20 '18 at 0:38