Which pyspark methods should I use for this table join?
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Article
|------|-----------|-------|
| ID | PARENT_ID | _data |
|------|-----------|-------|
| 12 | 34 | mom |
|------|-----------|-------|
| 5 | 34 | dad |
|------|-----------|-------|
Article_Meta
|-------|---------|------------|
| ID | USER_ID | COMMENT_ID |
|-------|---------|------------|
| 12 | [3] | [ 7, 8] |
|-------|---------|------------|
| 34 | [6] | [ 1, 2] |
|-------|---------|------------|
Result: Article + Article_Metadata
ID 12 has User ID 3 and 6 because
ID = Article_Meta#12 has User_ID 3 AND
ParentID = Article_Meta#34 has USER_ID 6
|------|-----------|-------|---------|------------|
| ID | PARENT_ID | _data | USER_ID | COMMENT_ID |
|------|-----------|-------|---------|------------|
| 12 | 34 | mom | [ 3, 6] |[7, 8, 1, 2]|
|------|-----------|-------|---------|------------|
| 5 | 34 | dad | [6] | [ 1, 2] |
|------|-----------|-------|---------|------------|
I have a table Article and I would like to join it with Article_Meta.
As you can see Article has an ID and a ParentID. Both this columns belong to the Article_Meta ID column.
How should I join Article with Article_Meta so that the USER_ID and COMMENT_ID are the combined result of the Article_PARENT_ID AND Article_ID in the MetaData Table? (Wich pyspark methods should I use?)
More Explanation:
In the Result Table Article #12 has USER_ID [3, 6] that's because Article #12 belongs to Article_Meta #12 and #34 (Parent ID)
apache-spark pyspark apache-spark-sql
asked 2 days ago
John Smith
2,59173767
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-2
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Article
|------|-----------|-------|
| ID | PARENT_ID | _data |
|------|-----------|-------|
| 12 | 34 | mom |
|------|-----------|-------|
| 5 | 34 | dad |
|------|-----------|-------|
Article_Meta
|-------|---------|------------|
| ID | USER_ID | COMMENT_ID |
|-------|---------|------------|
| 12 | [3] | [ 7, 8] |
|-------|---------|------------|
| 34 | [6] | [ 1, 2] |
|-------|---------|------------|
Result: Article + Article_Metadata
ID 12 has User ID 3 and 6 because
ID = Article_Meta#12 has User_ID 3 AND
ParentID = Article_Meta#34 has USER_ID 6
|------|-----------|-------|---------|------------|
| ID | PARENT_ID | _data | USER_ID | COMMENT_ID |
|------|-----------|-------|---------|------------|
| 12 | 34 | mom | [ 3, 6] |[7, 8, 1, 2]|
|------|-----------|-------|---------|------------|
| 5 | 34 | dad | [6] | [ 1, 2] |
|------|-----------|-------|---------|------------|
I have a table Article and I would like to join it with Article_Meta.
As you can see Article has an ID and a ParentID. Both this columns belong to the Article_Meta ID column.
How should I join Article with Article_Meta so that the USER_ID and COMMENT_ID are the combined result of the Article_PARENT_ID AND Article_ID in the MetaData Table? (Wich pyspark methods should I use?)
More Explanation:
In the Result Table Article #12 has USER_ID [3, 6] that's because Article #12 belongs to Article_Meta #12 and #34 (Parent ID)
apache-spark pyspark apache-spark-sql
asked 2 days ago
John Smith
2,59173767
add a comment |
up vote
-2
down vote
favorite
up vote
-2
down vote
favorite
Article
|------|-----------|-------|
| ID | PARENT_ID | _data |
|------|-----------|-------|
| 12 | 34 | mom |
|------|-----------|-------|
| 5 | 34 | dad |
|------|-----------|-------|
Article_Meta
|-------|---------|------------|
| ID | USER_ID | COMMENT_ID |
|-------|---------|------------|
| 12 | [3] | [ 7, 8] |
|-------|---------|------------|
| 34 | [6] | [ 1, 2] |
|-------|---------|------------|
Result: Article + Article_Metadata
ID 12 has User ID 3 and 6 because
ID = Article_Meta#12 has User_ID 3 AND
ParentID = Article_Meta#34 has USER_ID 6
|------|-----------|-------|---------|------------|
| ID | PARENT_ID | _data | USER_ID | COMMENT_ID |
|------|-----------|-------|---------|------------|
| 12 | 34 | mom | [ 3, 6] |[7, 8, 1, 2]|
|------|-----------|-------|---------|------------|
| 5 | 34 | dad | [6] | [ 1, 2] |
|------|-----------|-------|---------|------------|
I have a table Article and I would like to join it with Article_Meta.
As you can see Article has an ID and a ParentID. Both this columns belong to the Article_Meta ID column.
How should I join Article with Article_Meta so that the USER_ID and COMMENT_ID are the combined result of the Article_PARENT_ID AND Article_ID in the MetaData Table? (Wich pyspark methods should I use?)
More Explanation:
In the Result Table Article #12 has USER_ID [3, 6] that's because Article #12 belongs to Article_Meta #12 and #34 (Parent ID)
apache-spark pyspark apache-spark-sql
asked 2 days ago
John Smith
2,59173767
Article
|------|-----------|-------|
| ID | PARENT_ID | _data |
|------|-----------|-------|
| 12 | 34 | mom |
|------|-----------|-------|
| 5 | 34 | dad |
|------|-----------|-------|
Article_Meta
|-------|---------|------------|
| ID | USER_ID | COMMENT_ID |
|-------|---------|------------|
| 12 | [3] | [ 7, 8] |
|-------|---------|------------|
| 34 | [6] | [ 1, 2] |
|-------|---------|------------|
Result: Article + Article_Metadata
ID 12 has User ID 3 and 6 because
ID = Article_Meta#12 has User_ID 3 AND
ParentID = Article_Meta#34 has USER_ID 6
|------|-----------|-------|---------|------------|
| ID | PARENT_ID | _data | USER_ID | COMMENT_ID |
|------|-----------|-------|---------|------------|
| 12 | 34 | mom | [ 3, 6] |[7, 8, 1, 2]|
|------|-----------|-------|---------|------------|
| 5 | 34 | dad | [6] | [ 1, 2] |
|------|-----------|-------|---------|------------|
I have a table Article and I would like to join it with Article_Meta.
As you can see Article has an ID and a ParentID. Both this columns belong to the Article_Meta ID column.
How should I join Article with Article_Meta so that the USER_ID and COMMENT_ID are the combined result of the Article_PARENT_ID AND Article_ID in the MetaData Table? (Wich pyspark methods should I use?)
More Explanation:
In the Result Table Article #12 has USER_ID [3, 6] that's because Article #12 belongs to Article_Meta #12 and #34 (Parent ID)
apache-spark pyspark apache-spark-sql
apache-spark pyspark apache-spark-sql
asked 2 days ago
John Smith
2,59173767
asked 2 days ago
John Smith
2,59173767
asked 2 days ago
John Smith
2,59173767
asked 2 days ago
John Smith
2,59173767
asked 2 days ago
John Smith
2,59173767
2,59173767
add a comment |
add a comment |
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