Ignore above query. Its incorrect.
I have following pig script
A = LOAD 'textinput' using PigStorage() as (a0:chararray, a1:chararray, a2:chararray, a3:chararray, a4:chararray, a5:chararray, a6:chararray, a7:chararray, a8:chararray,a9:chararray);
describe A;
store A into 'output2' using PigStorage();
This works fine.
However when i modify the store statement to
store A into 'output3' using PigStorage() as (a0:chararray, a1:chararray, a2:chararray, a3:chararray, a4:chararray, a5:chararray, a6:chararray, a7:chararray, a8:chararray,a9:chararray);
It fails with below error
2013-05-04 11:49:56,296 [main] ERROR org.apache.pig.tools.grunt.Grunt - ERROR 1200: mismatched input 'as' expecting SEMI_COLON
You don't specify a schema when storing an output with pig. The schema of the alias you're storing is whatever it was when you created it. If you wished to change the way it's stored you could do something like
B = FOREACH A GENERATE (insert transformation here);
STORE B INTO 'output3';
If you wished to change the way PigStorage writes your alias to disk you could create your own StoreFunc
Related
I am trying to write a table into my data warehouse using the RPostgreSQL package
library(DBI)
library(RPostgreSQL)
pano = dbConnect(dbDriver("PostgreSQL"),
host = 'db.panoply.io',
port = '5439',
user = panoply_user,
password = panoply_pw,
dbname = mydb)
RPostgreSQL::dbWriteTable(pano, "mtcars", mtcars[1:5, ])
I am getting this error:
Error in postgresqlpqExec(new.con, sql4) :
RS-DBI driver: (could not Retrieve the result : ERROR: syntax error at or near "STDIN"
LINE 1: ..."hp","drat","wt","qsec","vs","am","gear","carb" ) FROM STDIN
^
)
The above code writes into Panoply as a 0 row, 0 byte table. Columns seem to be properly entered into Panoply but nothing else appears.
Fiest and most important redshift <> postgresql.
Redshift does not use the Postgres bulk loader. (so stdin is NOT allowed).
There are many options available which you should choose depending on your need, especially consider the volume of data.
For high volume of data you should write to s3 first and then use redshift copy command.
There are many options take a look at
https://github.com/sicarul/redshiftTools
for low volume see
inserting multiple records at once into Redshift with R
I am trying to load JSON file from Staging area (S3) into Stage table using COPY INTO command.
Table:
create or replace TABLE stage_tableA (
RAW_JSON VARIANT NOT NULL
);
Copy Command:
copy into stage_tableA from #stgS3/filename_45.gz file_format = (format_name = 'file_json')
Got the below error when executing the above (sample provided)
SQL Error [100069] [22P02]: Error parsing JSON: document is too large, max size 16777216 bytes If you would like to continue loading
when an error is encountered, use other values such as 'SKIP_FILE' or
'CONTINUE' for the ON_ERROR option. For more information on loading
options, please run 'info loading_data' in a SQL client.
When I had put "ON_ERROR=CONTINUE" , records got partially loaded, i.e until the record with more than max size. But no records after the Error record was loaded.
Was "ON_ERROR=CONTINUE" supposed to skip only the record that has max size and load records before and after it ?
Yes, the ON_ERROR=CONTINUE skips the offending line and continues to load the rest of the file.
To help us provide more insight, can you answer the following:
How many records are in your file?
How many got loaded?
At what line was the error first encountered?
You can find this information using the COPY_HISTORY() table function
Try setting the option strip_outer_array = true for file format and attempt the loading again.
The considerations for loading large size semi-structured data are documented in the below article:
https://docs.snowflake.com/en/user-guide/semistructured-considerations.html
I partially agree with Chris. The ON_ERROR=CONTINUE option only helps if the there are in fact more than 1 JSON objects in the file. If it's 1 massive object then you would simply not get an error or the record loaded when using ON_ERROR=CONTINUE.
If you know your JSON payload is smaller than 16mb then definitely try the strip_outer_array = true. Also, if your JSON has a lot of nulls ("NULL") as values use the STRIP_NULL_VALUES = TRUE as this will slim your payload as well. Hope that helps.
I am unable to query with .sql file in DataProcHiveOperator.
Though the documentation tells that we can query using file. Link of the documentation Here
It is working fine when I give query directly
Here is my sample code which is working fine with writing query directly:
HiveInsertingTable = DataProcHiveOperator(task_id='HiveInsertingTable',
gcp_conn_id='google_cloud_default',
query='CREATE TABLE TABLE_NAME(NAME STRING);',
cluster_name='cluster-name',
region='us-central1',
dag=dag)
Querying with file :
HiveInsertingTable = DataProcHiveOperator(task_id='HiveInsertingTable',
gcp_conn_id='google_cloud_default',
query='gs://us-central1-bucket/data/sample_hql.sql',
query_uri="gs://us-central1-bucket/data/sample_hql.sql
cluster_name='cluster-name',
region='us-central1',
dag=dag)
There is no error on sample_hql.sql script.
It is reading file location as a query and throwing me the error as:
Query: 'gs://bucketpath/filename.q'
Error occuring - cannot recognize input near 'gs' ':' '/'
Similar issue has also been raised Here
The issue is because you have passed query='gs://us-central1-bucket/data/sample_hql.sql' as well.
You should pass exactly 1 of query or queri_uri.
The code in your question has both of them, so remove query or use the following code:
HiveInsertingTable = DataProcHiveOperator(task_id='HiveInsertingTable',
gcp_conn_id='google_cloud_default',
query_uri="gs://us-central1-bucket/data/sample_hql.sql",
cluster_name='cluster-name',
region='us-central1',
dag=dag)
I'm trying to parse a Date in a Pig script and i got the following error "Hadoop does not return any error message".
Here is the Date format example : 3/9/16 2:50 PM
And here is how I parse it :
data = LOAD 'cleaned.txt'
AS (Date, Block, Primary_Type, Description, Location_Description, Arrest, Domestic, District, Year);
times = FOREACH data GENERATE ToDate(Date, 'M/d/yy h:mm a') As Time;
You can see the data file here
Do you have any idea ?
Thanks
EDIT:
It look like the error is caused by the STORE command on "times".
If I do a DUMP then I got:
ERROR 1066: Unable to open iterator for alias times
It happen only when I use the ToDate function, I have other scripts that work perfectly.
First of all, you need to specify the loader in the LOAD statement:
USING PigStorage('\t')
I assumed that you're using tab separator.
Than if you have no schema specify the schema with type!
So you're load statement will be sg like this:
data = LOAD 'SO/date2parse.txt' USING PigStorage('\t') AS (Date:chararray, Block:chararray, Primary_Type:chararray, Description:chararray, Location_Description:chararray, Arrest:chararray, Domestic:chararray, District:chararray, Year:chararray);
For now I just use chararray type for everything, but you have to specify the type what is the right representation for you.
After this the date conversion just works fine as you wrote:
(2016-03-09T23:55:00.000Z)
(2016-03-09T23:55:00.000Z)
(2016-03-09T23:55:00.000Z)
My test script:
data = LOAD 'SO/date2parse.txt' USING PigStorage('\t') AS (Date:chararray, Block:chararray, Primary_Type:chararray, Description:chararray, Location_Description:chararray, Arrest:chararray, Domestic:chararray, District:chararray, Year:chararray);
times = FOREACH data GENERATE ToDate(Date, 'M/d/yy h:mm a') As Time;
DUMP times;
UPDATE:
Some explanation
By the way the default loader is pig storage
PigStorage is the default load function for the LOAD operator.
but it's nicer to specify.
The original issue caused by the lack of datatype
If you don't assign types, fields default to type bytearray
so the ToDate failed on the input type.
I have a very simple Pentaho Kettle transformation that causes a strange error. It consists of reading a field X from a CSV, add a field Y, set Y=X and finally write it back to another CSV.
Here you can see the steps and the configuration for them:
You can also download the ktr file from here. The input data is just this:
1
2
3
When I run this transformation, I get this error message:
ERROR (version 5.4.0.1-130, build 1 from 2015-06-14_12-34-55 by buildguy) : Unexpected error
ERROR (version 5.4.0.1-130, build 1 from 2015-06-14_12-34-55 by buildguy) : org.pentaho.di.core.exception.KettleStepException:
Error writing line
Error writing field content to file
Y Number : There was a data type error: the data type of [B object [[B©b4136a] does not correspond to value meta [Number]
at org.pentaho.di.trans.steps.textfiIeoutput.TextFiIeOutput.writeRowToFile(TextFiIeOutput.java:273)
at org.pentaho.di.trans.steps.textfiIeoutput.TextFileOutput.processRow(TextFiIeOutput.java:195)
at org.pentaho.di.trans.step.RunThread.run(RunThread.java:62)
atjava.Iang.Thread.run(Unknown Source)
Caused by: org.pentaho.di.core.exception.KettleStepException:
Error writing field content to file
Y Number : There was a data type error: the data type of [B object [[B©b4136a] does not correspond to value meta [Number]
at org.pentaho.di.trans.steps.textfiIeoutput.TextFiIeOutput.writeField(TextFileOutput.java:435)
at org.pentaho.di.trans.steps.textfiIeoutput.TextFiIeOutput.writeRowToFile(TextFiIeOutput.java:249)
3 more
Caused by: org.pentaho.di.core.exception.KettleVaIueException:
Y Number : There was a data type error: the data type of [B object [[B©b4136a] does not correspond to value meta [Number]
at org.pentaho.di.core.row.vaIue.VaIueMetaBase.getBinaryString(VaIueMetaBase.java:2185)
at org.pentaho.di.trans.steps.textfiIeoutput.TextFiIeOutput.formatField(TextFiIeOutput.java:290)
at org.pentaho.di.trans.steps.textfiIeoutput.TextFiIeOutput.writeField(TextFileOutput.java:392)
4 more
All of the above lines start with 2015/09/23 12:51:18 - Text file output.0 -, but I edited it out for brevity. I think the relevant, and confusing, part of the error message is this:
Y Number : There was a data type error: the data type of [B object [[B©b4136a] does not correspond to value meta [Number]
Some further notes:
If I bypass the set field value step by using the lower hop instead, the transformation finish without errors. This leads me to believe that it is the set field value step that causes the problem.
If I replace the CSV file input with a data frame with the same data (1,2,3) everything works just fine.
If I replace the file output step with a dummy the transformation finish without errors. However, if I preview the dummy, it causes a similar error and the field Y has the value <null> on all three rows.
Before I created this MCVE I got the error on all sorts of seemingly random steps, even when there was no file output present. So I do not think this is related to the file output.
If I change the format from Number to Integer, nothing changes. But if I change it to string the transformations finish without errors, and I get this output:
X;Y
1;[B#49e96951
2;[B#7b016abf
3;[B#1a0760b0
Is this a bug? Am I doing something wrong? How can I make this work?
It's because of lazy conversion. Turn it off. This is behaving exactly as designed - although admittedly the error and user experience could be improved.
Lazy conversion must not be used when you need to access the field value in your transformation. That's exactly what it does. The default should probably be off rather than on.
If your field is going directly to a database, then use it and it will be faster.
You can even have "partially lazy" streams, where you use lazy conversion for speed, but then use select values step, to "un-lazify" the fields you want to access, whilst the remainder remain lazy.
Cunning huh?