Why the result is empty after merging two streams in Spark 2.4?
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I use Spark 2.4 in order to join two streams. The problem is that the result is empty.
I load streaming data from folders:
data/1
[
{"id1": 77,"name1": "aaa","timestamp": 1532609003},
{"id1": 77,"name1": "xxx","timestamp": 1532609005},
{"id1": 78,"name1": "xxx","timestamp": 1532609005}
]
data/2
[
{"id2": 77,"name2": "yyy", "timestamp2": 1532609000}
]
My code:
schema1 = StructType([
StructField("id1", IntegerType()),
StructField("name1", StringType()),
StructField("timestamp1", TimestampType()))
])
schema2 = StructType([
StructField("id2", IntegerType()),
StructField("name2", StringType()),
StructField("timestamp2", TimestampType()))
])
ds1 = spark
.readStream
.format("json")
.schema(schema1)
.load("data/1")
.withWatermark("timestamp1", "2 minutes")
ds2 = spark
.readStream
.format("json")
.schema(schema2)
.load("data/2")
.withWatermark("timestamp2", "2 minutes")
ds_joined = ds1.join(
ds2,
func.expr("""
id1 = id2 AND
timestamp1 >= timestamp2 AND
timestamp1 <= timestamp2 + interval 2 minutes
"""),
"leftOuter"
).fillna(0)
query = ds_joined
.writeStream
.format('console')
.start()
query.awaitTermination()
As it can be seen, I used a watermark of 2 minutes. Therefore I do not understand my I get an empty joined dataset.
Expected output:
id1 id2 name1 name2 timestamp1 timestamp2
77 77 aaa yyy 1532609003 1532609000
77 77 xxx yyy 1532609005 1532609000
78 0 xxx 0 1532609005 0
python apache-spark pyspark spark-structured-streaming
asked Nov 24 '18 at 21:14
MozimakiMozimaki
524
add a comment |
0
I use Spark 2.4 in order to join two streams. The problem is that the result is empty.
I load streaming data from folders:
data/1
[
{"id1": 77,"name1": "aaa","timestamp": 1532609003},
{"id1": 77,"name1": "xxx","timestamp": 1532609005},
{"id1": 78,"name1": "xxx","timestamp": 1532609005}
]
data/2
[
{"id2": 77,"name2": "yyy", "timestamp2": 1532609000}
]
My code:
schema1 = StructType([
StructField("id1", IntegerType()),
StructField("name1", StringType()),
StructField("timestamp1", TimestampType()))
])
schema2 = StructType([
StructField("id2", IntegerType()),
StructField("name2", StringType()),
StructField("timestamp2", TimestampType()))
])
ds1 = spark
.readStream
.format("json")
.schema(schema1)
.load("data/1")
.withWatermark("timestamp1", "2 minutes")
ds2 = spark
.readStream
.format("json")
.schema(schema2)
.load("data/2")
.withWatermark("timestamp2", "2 minutes")
ds_joined = ds1.join(
ds2,
func.expr("""
id1 = id2 AND
timestamp1 >= timestamp2 AND
timestamp1 <= timestamp2 + interval 2 minutes
"""),
"leftOuter"
).fillna(0)
query = ds_joined
.writeStream
.format('console')
.start()
query.awaitTermination()
As it can be seen, I used a watermark of 2 minutes. Therefore I do not understand my I get an empty joined dataset.
Expected output:
id1 id2 name1 name2 timestamp1 timestamp2
77 77 aaa yyy 1532609003 1532609000
77 77 xxx yyy 1532609005 1532609000
78 0 xxx 0 1532609005 0
python apache-spark pyspark spark-structured-streaming
asked Nov 24 '18 at 21:14
MozimakiMozimaki
524
Ignoring syntax errors, which I assume are not present in you original code a) Input is not a valid JSONL, so you should use multiline option b) schema doesn't match the data, as integer is not valid input for timestamp c) even if you considered values as epoch timestamps and casted directly (StructField("timestamp1", "long"))andcol(""timestamp1").cast("timestamp")), the latest value is July or, so would be discarded with 2 minute watermark. There might be some other problem as well, not obvious at first glance.
– user6910411
Nov 24 '18 at 21:31
add a comment |
0
0
0
I use Spark 2.4 in order to join two streams. The problem is that the result is empty.
I load streaming data from folders:
data/1
[
{"id1": 77,"name1": "aaa","timestamp": 1532609003},
{"id1": 77,"name1": "xxx","timestamp": 1532609005},
{"id1": 78,"name1": "xxx","timestamp": 1532609005}
]
data/2
[
{"id2": 77,"name2": "yyy", "timestamp2": 1532609000}
]
My code:
schema1 = StructType([
StructField("id1", IntegerType()),
StructField("name1", StringType()),
StructField("timestamp1", TimestampType()))
])
schema2 = StructType([
StructField("id2", IntegerType()),
StructField("name2", StringType()),
StructField("timestamp2", TimestampType()))
])
ds1 = spark
.readStream
.format("json")
.schema(schema1)
.load("data/1")
.withWatermark("timestamp1", "2 minutes")
ds2 = spark
.readStream
.format("json")
.schema(schema2)
.load("data/2")
.withWatermark("timestamp2", "2 minutes")
ds_joined = ds1.join(
ds2,
func.expr("""
id1 = id2 AND
timestamp1 >= timestamp2 AND
timestamp1 <= timestamp2 + interval 2 minutes
"""),
"leftOuter"
).fillna(0)
query = ds_joined
.writeStream
.format('console')
.start()
query.awaitTermination()
As it can be seen, I used a watermark of 2 minutes. Therefore I do not understand my I get an empty joined dataset.
Expected output:
id1 id2 name1 name2 timestamp1 timestamp2
77 77 aaa yyy 1532609003 1532609000
77 77 xxx yyy 1532609005 1532609000
78 0 xxx 0 1532609005 0
python apache-spark pyspark spark-structured-streaming
asked Nov 24 '18 at 21:14
MozimakiMozimaki
524
I use Spark 2.4 in order to join two streams. The problem is that the result is empty.
I load streaming data from folders:
data/1
[
{"id1": 77,"name1": "aaa","timestamp": 1532609003},
{"id1": 77,"name1": "xxx","timestamp": 1532609005},
{"id1": 78,"name1": "xxx","timestamp": 1532609005}
]
data/2
[
{"id2": 77,"name2": "yyy", "timestamp2": 1532609000}
]
My code:
schema1 = StructType([
StructField("id1", IntegerType()),
StructField("name1", StringType()),
StructField("timestamp1", TimestampType()))
])
schema2 = StructType([
StructField("id2", IntegerType()),
StructField("name2", StringType()),
StructField("timestamp2", TimestampType()))
])
ds1 = spark
.readStream
.format("json")
.schema(schema1)
.load("data/1")
.withWatermark("timestamp1", "2 minutes")
ds2 = spark
.readStream
.format("json")
.schema(schema2)
.load("data/2")
.withWatermark("timestamp2", "2 minutes")
ds_joined = ds1.join(
ds2,
func.expr("""
id1 = id2 AND
timestamp1 >= timestamp2 AND
timestamp1 <= timestamp2 + interval 2 minutes
"""),
"leftOuter"
).fillna(0)
query = ds_joined
.writeStream
.format('console')
.start()
query.awaitTermination()
As it can be seen, I used a watermark of 2 minutes. Therefore I do not understand my I get an empty joined dataset.
Expected output:
id1 id2 name1 name2 timestamp1 timestamp2
77 77 aaa yyy 1532609003 1532609000
77 77 xxx yyy 1532609005 1532609000
78 0 xxx 0 1532609005 0
python apache-spark pyspark spark-structured-streaming
python apache-spark pyspark spark-structured-streaming
asked Nov 24 '18 at 21:14
MozimakiMozimaki
524
asked Nov 24 '18 at 21:14
MozimakiMozimaki
524
asked Nov 24 '18 at 21:14
MozimakiMozimaki
524
asked Nov 24 '18 at 21:14
MozimakiMozimaki
524
asked Nov 24 '18 at 21:14
MozimakiMozimaki
524
524
Ignoring syntax errors, which I assume are not present in you original code a) Input is not a valid JSONL, so you should use multiline option b) schema doesn't match the data, as integer is not valid input for timestamp c) even if you considered values as epoch timestamps and casted directly (StructField("timestamp1", "long"))andcol(""timestamp1").cast("timestamp")), the latest value is July or, so would be discarded with 2 minute watermark. There might be some other problem as well, not obvious at first glance.
– user6910411
Nov 24 '18 at 21:31
add a comment |
Ignoring syntax errors, which I assume are not present in you original code a) Input is not a valid JSONL, so you should use multiline option b) schema doesn't match the data, as integer is not valid input for timestamp c) even if you considered values as epoch timestamps and casted directly (StructField("timestamp1", "long"))andcol(""timestamp1").cast("timestamp")), the latest value is July or, so would be discarded with 2 minute watermark. There might be some other problem as well, not obvious at first glance.
– user6910411
Nov 24 '18 at 21:31
Ignoring syntax errors, which I assume are not present in you original code a) Input is not a valid JSONL, so you should use multiline option b) schema doesn't match the data, as integer is not valid input for timestamp c) even if you considered values as epoch timestamps and casted directly (
StructField("timestamp1", "long")) and col(""timestamp1").cast("timestamp")), the latest value is July or, so would be discarded with 2 minute watermark. There might be some other problem as well, not obvious at first glance.– user6910411
Nov 24 '18 at 21:31
Ignoring syntax errors, which I assume are not present in you original code a) Input is not a valid JSONL, so you should use multiline option b) schema doesn't match the data, as integer is not valid input for timestamp c) even if you considered values as epoch timestamps and casted directly (
StructField("timestamp1", "long")) and col(""timestamp1").cast("timestamp")), the latest value is July or, so would be discarded with 2 minute watermark. There might be some other problem as well, not obvious at first glance.– user6910411
Nov 24 '18 at 21:31
add a comment |
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Ignoring syntax errors, which I assume are not present in you original code a) Input is not a valid JSONL, so you should use multiline option b) schema doesn't match the data, as integer is not valid input for timestamp c) even if you considered values as epoch timestamps and casted directly (
StructField("timestamp1", "long"))andcol(""timestamp1").cast("timestamp")), the latest value is July or, so would be discarded with 2 minute watermark. There might be some other problem as well, not obvious at first glance.– user6910411
Nov 24 '18 at 21:31