Hello,
Currently, there is no NaiveBayes implementation for MLpipeline. I couldn't
find the JIRA ticket related to it too (or maybe I missed).
Is there a plan to implement it? If no one has the bandwidth, I can work on
it.
Thanks.
Justin
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Done.
https://issues.apache.org/jira/browse/SPARK-8420
Justin
On Wed, Jun 17, 2015 at 4:06 PM, Xiangrui Meng men...@gmail.com wrote:
That sounds like a bug. Could you create a JIRA and ping Yin Huai
(cc'ed). -Xiangrui
On Wed, May 27, 2015 at 12:57 AM, Justin Yip yipjus...@prediction.io
Hello,
I am using 1.4.0 and found the following weird behavior.
This case works fine:
scala sc.parallelize(Seq((1,2), (3, 100))).toDF.withColumn(index,
rand(30)).show()
+--+---+---+
|_1| _2| index|
+--+---+---+
| 1| 2| 0.6662967911724369|
|
Hello,
I have a question with Spark 1.4 ml library. In the copy function, it is
stated that the default implementation doesn't work of Params doesn't work
for models. (
https://github.com/apache/spark/blob/master/mllib/src/main/scala/org/apache/spark/ml/Model.scala#L49
)
As a result, some
Hello,
I am trying out 1.4.0 and notice there are some differences in behavior
with Timestamp between 1.3.1 and 1.4.0.
In 1.3.1, I can compare a Timestamp with string.
scala val df = sqlContext.createDataFrame(Seq((1,
Timestamp.valueOf(2015-01-01 00:00:00)), (2,
Timestamp.valueOf(2014-01-01
Hello,
I am trying to build scala doc from the 1.4 branch. But it failed due to
[error] (sql/compile:compile) java.lang.AssertionError: assertion failed:
List(object package$DebugNode, object package$DebugNode)
I followed the instruction on github
Hello,
I am using MLPipeline. I would like to extract the best parameter found by
CrossValidator. But I cannot find much document about how to do it. Can
anyone give me some pointers?
Thanks.
Justin
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Hello,
I would like ask know if there are recommended ways of preventing ambiguous
columns when joining dataframes. When we join dataframes, it usually happen
we join the column with identical name. I could have rename the columns on
the right data frame, as described in the following code. Is
be possible to write udafs in
similar lines of sum/min etc.
On Fri, May 15, 2015 at 5:49 AM, Justin Yip yipjus...@prediction.io
wrote:
Hello,
May I know if these is way to implement aggregate function for grouped
data in DataFrame? I dug into the doc but didn't find any apart from the
UDF
: DataFrame, usingColumn: String):
DataFrame*
df.join(df1, _1)
This has the added benefit of only outputting a single _1 column.
On Fri, May 15, 2015 at 3:44 PM, Justin Yip yipjus...@prediction.io
wrote:
Hello,
I would like ask know if there are recommended ways of preventing
ambiguous columns
Hello,
May I know if these is way to implement aggregate function for grouped data
in DataFrame? I dug into the doc but didn't find any apart from the UDF
functions which applies on a Row. Maybe I have missed something. Thanks.
Justin
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Hello,
I would like to add a StructType to DataFrame. What would be the best way
to do it? Not sure if it is possible using withColumn. A possible way is to
convert the dataframe into a RDD[Row], add the struct and then convert it
back to dataframe. But that seems an overkill.
I guess I may have
After some trial and error, using DataType solves the problem:
df.withColumn(millis, $eventTime.cast(
org.apache.spark.sql.types.LongType) * 1000)
Justin
On Thu, Apr 30, 2015 at 3:41 PM, Justin Yip yipjus...@prediction.io wrote:
Hello,
I was able to cast a timestamp into long using
Hello,
I was able to cast a timestamp into long using
df.withColumn(millis, $eventTime.cast(long) * 1000)
in spark 1.3.0.
However, this statement returns a failure with spark 1.3.1. I got the
following exception:
Exception in thread main org.apache.spark.sql.types.DataTypeException:
Unsupported
Hello,
I would like rename a column after aggregation. In the following code, the
column name is SUM(_1#179), is there a way to rename it to a more
friendly name?
scala val d = sqlContext.createDataFrame(Seq((1, 2), (1, 3), (2, 10)))
scala d.groupBy(_1).sum().printSchema
root
|-- _1: integer
://github.com/apache/spark/blob/master/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/HiveTypeCoercion.scala#L144
On Tue, Apr 7, 2015 at 5:00 PM, Justin Yip yipjus...@prediction.io
wrote:
Hello,
I am experimenting with DataFrame. I tried to construct two DataFrames
with:
1
Hello,
I would like to know if there is a way of catching exception throw from
executor exception from the driver program. Here is an example:
try {
val x = sc.parallelize(Seq(1,2,3)).map(e = e / 0).collect
} catch {
case e: SparkException = {
println(sERROR: $e)
println(sCAUSE:
Hello,
I am experimenting with DataFrame. I tried to construct two DataFrames with:
1. case class A(a: Int, b: String)
scala adf.printSchema()
root
|-- a: integer (nullable = false)
|-- b: string (nullable = true)
2. case class B(a: String, c: Int)
scala bdf.printSchema()
root
|-- a: string
Cheng, this is great info. I have a follow up question. There are a few
very common data types (i.e. Joda DateTime) that is not directly supported
by SparkSQL. Do you know if there are any plans for accommodating some
common data types in SparkSQL? They don't need to be a first class
datatype, but
Hello,
The DataFrame documentation always uses $columnX to annotates a column.
But I cannot find much information about it. Maybe I have missed something.
Can anyone point me to the doc about the $, if there is any?
Thanks.
Justin
Hello,
Are there any restriction in the column name? I tried to use ., but
sqlContext.sql cannot find the column. I would guess that . is tricky as
this affects accessing StructType, but are there any more restriction on
column name?
scala case class A(a: Int)
defined class A
scala
, Michael Armbrust mich...@databricks.com
wrote:
In HiveQL, you should be able to express this as:
SELECT ... FROM table GROUP BY m['SomeKey']
On Sat, Apr 4, 2015 at 5:25 PM, Justin Yip yipjus...@prediction.io
wrote:
Hello,
I have a case class like this:
case class A(
m: Map[Long, Long
Hello,
I am experimenting with DataFrame. I tried to construct two DataFrames with:
1. case class A(a: Int, b: String)
scala adf.printSchema()
root
|-- a: integer (nullable = false)
|-- b: string (nullable = true)
2. case class B(a: String, c: Int)
scala bdf.printSchema()
root
|-- a: string
Hello,
I have a parquet file of around 55M rows (~ 1G on disk). Performing simple
grouping operation is pretty efficient (I get results within 10 seconds).
However, after called DataFrame.cache, I observe a significant performance
degrade, the same operation now takes 3+ minutes.
My hunch is
The schema has a StructType.
Justin
On Tue, Apr 7, 2015 at 6:58 PM, Yin Huai yh...@databricks.com wrote:
Hi Justin,
Does the schema of your data have any decimal, array, map, or struct type?
Thanks,
Yin
On Tue, Apr 7, 2015 at 6:31 PM, Justin Yip yipjus...@prediction.io
wrote:
Hello
the improvement.
On Tue, Apr 7, 2015 at 6:59 PM, Justin Yip yipjus...@prediction.io
wrote:
The schema has a StructType.
Justin
On Tue, Apr 7, 2015 at 6:58 PM, Yin Huai yh...@databricks.com wrote:
Hi Justin,
Does the schema of your data have any decimal, array, map, or struct
type?
Thanks,
Yin
Hello,
I have a case class like this:
case class A(
m: Map[Long, Long],
...
)
and constructed a DataFrame from Seq[A].
I would like to perform a groupBy on A.m(SomeKey). I can implement a UDF,
create a new Column then invoke a groupBy on the new Column. But is it the
idiomatic way of doing
Hello Zhou,
You can look at the recommendation template
http://templates.prediction.io/PredictionIO/template-scala-parallel-recommendation
of PredictionIO. PredictionIO is built on the top of spark. And this
template illustrates how you can save the ALS model to HDFS and the reload
it later.
setCheckpointInterval to solve this
problem, which is available in the current master and 1.3.1 (to be
released soon). Btw, do you find 80 iterations are needed for
convergence? -Xiangrui
On Wed, Apr 1, 2015 at 11:54 PM, Justin Yip yipjus...@prediction.io
wrote:
Hello,
I have been using Mllib's ALS in 1.2
Hello,
I have been using Mllib's ALS in 1.2 and it works quite well. I have just
upgraded to 1.3 and I encountered stackoverflow problem.
After some digging, I realized that when the iteration ~35, I will get
overflow problem. However, I can get at least 80 iterations with ALS in 1.2.
Is there
Hello,
I have persisted a RDD[T] to disk through saveAsObjectFile. Then I
changed the implementation of T. When I read the file with sc.objectFile
using the new binary, I got the exception of java.io.InvalidClassException,
which is expected.
I try to catch this error via SparkException in the
Hello,
From accumulator documentation, it says that if the accumulator is named,
it will be displayed in the WebUI. However, I cannot find it anywhere.
Do I need to specify anything in the spark ui config?
Thanks.
Justin
Found it. Thanks Patrick.
Justin
On Wed, Jan 14, 2015 at 10:38 PM, Patrick Wendell pwend...@gmail.com
wrote:
It should appear in the page for any stage in which accumulators are
updated.
On Wed, Jan 14, 2015 at 6:46 PM, Justin Yip yipjus...@prediction.io
wrote:
Hello,
From
Xuelin,
There is a function called emtpyRDD under spark context
http://spark.apache.org/docs/latest/api/scala/index.html#org.apache.spark.SparkContext
which
serves this purpose.
Justin
On Mon, Jan 12, 2015 at 9:50 PM, Xuelin Cao xuelincao2...@gmail.com wrote:
Hi,
I'd like to create a
Hello,
I am looking into a couple of MLLib data files in
https://github.com/apache/spark/tree/master/data/mllib. But I cannot find
any explanation for these files? Does anyone know if they are documented?
Thanks.
Justin
On Sun, Jun 22, 2014 at 3:24 PM, Justin Yip yipjus...@gmail.com wrote:
Hi Shuo,
Yes. I was reading the guide as well as the sample code.
For example, in
http://spark.apache.org/docs/latest/mllib-linear-methods.html#linear-support-vector-machine-svm,
now where in the github repository I
.
Justin
On Sun, Jun 22, 2014 at 2:40 PM, Shuo Xiang shuoxiang...@gmail.com wrote:
Hi, you might find http://spark.apache.org/docs/latest/mllib-guide.html
helpful.
On Sun, Jun 22, 2014 at 2:35 PM, Justin Yip yipjus...@gmail.com wrote:
Hello,
I am looking into a couple of MLLib data files
I see. That's good. Thanks.
Justin
On Sun, Jun 22, 2014 at 4:59 PM, Evan Sparks evan.spa...@gmail.com wrote:
Oh, and the movie lens one is userid::movieid::rating
- Evan
On Jun 22, 2014, at 3:35 PM, Justin Yip yipjus...@gmail.com wrote:
Hello,
I am looking into a couple of MLLib data
Hello,
I have been playing around with mllib's decision tree library. It is
working great, thanks.
I have a question regarding overfitting. It appears to me that the current
implementation doesn't allows user to specify the minimum number of samples
per node. This results in some nodes only
Hello,
I have been using Externalizer from Chill to as serialization wrapper. It
appears to me that Spark have some conflict with the classloader with
Chill. I have the (a simplified version) following program:
import java.io._
import com.twitter.chill.Externalizer
class X(val i: Int) {
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