thank you for reply,Shreya:
It's because the files is too small and hdfs dosen't like small file . 
for your question. yes I want to create ExternalTable on the parquetfile 
floder. And how to use fragmented files as you mention?


the tests case as below:
bin/spark-shell --master yarn --deploy-mode client --driver-memory 6g 
--executor-memory 8g --executor-cores 2 --num-executors 4
val df = spark.read.parquet("/parquetdata/weixin/biz-tag-relation/")
df.createOrReplaceTempView("biztag")             #almost 70M   3673411 rows
val df2 = spark.read.parquet("/parquetdata/weixin/biz/month=201608")
df2.createOrReplaceTempView("biz1608")        #almost 90M   381700  rows
for(i <- 1 to 61) {
      val dft = spark.sql(s"select biz1608.*,biztag.tag_id from biz1608 left 
join biztag on biz1608.bid = biztag.biz_id where biztag.tag_id = ${i}")
      dft.coalesce(1).write.parquet(s"/parquetdata/weixin/biztags/biztag${i}")
 }





At 2016-11-10 15:47:02, "Shreya Agarwal" <shrey...@microsoft.com> wrote:


Is there a reason you want to merge the files? The reason you are getting 
errors (afaik) is because when you try to coalesce and then write, you are 
forcing all the content to reside on one executor, and the size of data is 
exceeding the memory you have for storage in your executor, hence causing the 
container to be killed. We can confirm this if you provide the specs of your 
cluster. The whole purpose of multiple files is so that each executor can write 
its partition out in parallel, without having to collect the data in one place.

 

Not to mention that it’ll make your write incredibly slow and also it’ll take 
away all the speed of reading in the data from a parquet as there won’t be any 
parallelism at the time of input (if you try to input this parquet).

 

Again, the important question is – Why do you need it to be one file? Are you 
planning to use it externally? If yes, can you not use fragmented files there? 
If the data is too big for the Spark executor, it’ll most certainly be too much 
for JRE or any other runtime  to load in memory on a single box.

 

From: lk_spark [mailto:lk_sp...@163.com]
Sent: Wednesday, November 9, 2016 11:29 PM
To: user.spark <user@spark.apache.org>
Subject: how to merge dataframe write output files

 

hi,all:

    when I call api df.write.parquet ,there is alot of small files :   how can 
I merge then into on file ? I tried df.coalesce(1).write.parquet ,but it will 
get error some times 

Container exited with a non-zero exit code 143

more an more... 

-rw-r--r--   2 hadoop supergroup     14.5 K 2016-11-10 15:11 
/parquetdata/weixin/biztags/biztag2/part-r-00165-0f61afe4-23e8-40bb-b30b-09652ca677bc.snappy.parquet
-rw-r--r--   2 hadoop supergroup     16.4 K 2016-11-10 15:11 
/parquetdata/weixin/biztags/biztag2/part-r-00166-0f61afe4-23e8-40bb-b30b-09652ca677bc.snappy.parquet
-rw-r--r--   2 hadoop supergroup     17.1 K 2016-11-10 15:11 
/parquetdata/weixin/biztags/biztag2/part-r-00167-0f61afe4-23e8-40bb-b30b-09652ca677bc.snappy.parquet
-rw-r--r--   2 hadoop supergroup     14.2 K 2016-11-10 15:11 
/parquetdata/weixin/biztags/biztag2/part-r-00168-0f61afe4-23e8-40bb-b30b-09652ca677bc.snappy.parquet
-rw-r--r--   2 hadoop supergroup     15.7 K 2016-11-10 15:11 
/parquetdata/weixin/biztags/biztag2/part-r-00169-0f61afe4-23e8-40bb-b30b-09652ca677bc.snappy.parquet
-rw-r--r--   2 hadoop supergroup     14.4 K 2016-11-10 15:11 
/parquetdata/weixin/biztags/biztag2/part-r-00170-0f61afe4-23e8-40bb-b30b-09652ca677bc.snappy.parquet
-rw-r--r--   2 hadoop supergroup     17.1 K 2016-11-10 15:11 
/parquetdata/weixin/biztags/biztag2/part-r-00171-0f61afe4-23e8-40bb-b30b-09652ca677bc.snappy.parquet
-rw-r--r--   2 hadoop supergroup     15.7 K 2016-11-10 15:11 
/parquetdata/weixin/biztags/biztag2/part-r-00172-0f61afe4-23e8-40bb-b30b-09652ca677bc.snappy.parquet
-rw-r--r--   2 hadoop supergroup     16.0 K 2016-11-10 15:11 
/parquetdata/weixin/biztags/biztag2/part-r-00173-0f61afe4-23e8-40bb-b30b-09652ca677bc.snappy.parquet
-rw-r--r--   2 hadoop supergroup     17.1 K 2016-11-10 15:11 
/parquetdata/weixin/biztags/biztag2/part-r-00174-0f61afe4-23e8-40bb-b30b-09652ca677bc.snappy.parquet
-rw-r--r--   2 hadoop supergroup     14.0 K 2016-11-10 15:11 
/parquetdata/weixin/biztags/biztag2/part-r-00175-0f61afe4-23e8-40bb-b30b-09652ca677bc.snappy.parquet
-rw-r--r--   2 hadoop supergroup     15.7 K 2016-11-10 15:11 
/parquetdata/weixin/biztags/biztag2/part-r-00176-0f61afe4-23e8-40bb-b30b-09652ca677bc

more an more... 

2016-11-10

lk_spark

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