davidrabinowitz commented on pull request #30071:
URL: https://github.com/apache/spark/pull/30071#issuecomment-721355772
@HyukjinKwon
Should I create another PR aimed at master?
In order to test it first you need to create a table in BigQuery in the
following manner:
```
bq load --source_format NEWLINE_DELIMITED_JSON <TABLE> vector_test.data.json
vector_test.schema.json
```
The files are:
- vector_test.data.json:
```
{"name":"row1","num":"1","vector":{"type":"1","indices":[],"values":[1,2,3]}}
{"name":"row2","num":"2","vector":{"type":"1","indices":[],"values":[4,5,6]}}
{"name":"row3","num":"3","vector":{"type":"1","indices":[],"values":[7,8,9]}}
```
- vector_test.schema.json:
```
[
{
"mode": "NULLABLE",
"name": "name",
"type": "STRING"
},
{
"mode": "NULLABLE",
"name": "num",
"type": "INTEGER"
},
{
"description": "{spark.type=vector}",
"fields": [
{
"mode": "NULLABLE",
"name": "type",
"type": "INTEGER"
},
{
"mode": "NULLABLE",
"name": "size",
"type": "INTEGER"
},
{
"mode": "REPEATED",
"name": "indices",
"type": "INTEGER"
},
{
"mode": "REPEATED",
"name": "values",
"type": "FLOAT"
}
],
"mode": "NULLABLE",
"name": "vector",
"type": "RECORD"
}
]
```
A GCP account is needed for that, but the amount of data and operation are
well in the free tier.
Run `spark-shell --packages
com.google.cloud.spark:spark-bigquery-with-dependencies_2.11:0.17.3` and enter
the following commands:
```
val df =
spark.read.format("com.google.cloud.spark.bigquery.v2.BigQueryDataSourceV2").load("<TABLE>")
df.schema()
df.show()
```
Notice that when the format is changed to `bigquery` another path is used
which does not rely on the code generator and hence does not suffer from this
issue.
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