I often have a large block of HiveQL that I want to run multiple times with different settings for some variables.
A simple example would be:
set mindate='2015-01-01 00:00:00'
set maxdate='2015-04-01 00:00:00'
select * from my_table where the_date between ${hiveconf:mindate} and ${hiveconf:maxdate}
Which is then run via hive -f myfile.sql > myout.log
Later, I would like to change the variables and re-run. I also want a record of what values the variables had each time I ran.
So I currently make copies of the HiveQL file that are the same except for the variable values. This is obviously error-prone, however, because if I need to change the actual HiveQL, then I have to change it in every file.
Ideally, I could store all my settings a JSON file (or whatever) and have my HiveQL file be totally dynamic. Is there any way to do this?
Set your variables in the config file and load this file in your hql script:
source /path_to_your_config_file/config.hql;
Related
There are records in my source text file with invalid date values. The invalid date values are inconsistent in format due to manual entry. I still want to load all of these records, but I want to replace the invalid date value with a null.
Please let me know if/how this is possible via SQLLDR control file commands. I want to avoid creating any custom functions. Something simple that generally refers to errors/exceptions and that works (unlike the below) is ideal:
DATE "MM/DD/YYYY" NULLIF (FROM_DOS=EXCEPTION)
Thanks!
As far as I can tell, that won't go in a single pass. I'd suggest you to try a relatively simple approach:
load the original data "as is"
rows with invalid dates won't be loaded, but will end in the .BAD file
then modify the control file:
source will now be the .BAD file
load NULL into the date column (FILLER might help)
Alternatively, you might use the source file as an external table and write (PL/)SQL against it to load data into the target table. It allows you to actually code whatever you want, but - as you said you don't want to create a custom function (which would decide whether the input data is - or is not - a valid DATE value), I presume you'd rather skip that option.
I want to use an external table to load a csv file as it's very convenient, but the problem is how do i make sure i don't load the same file twice in a row? i can't validate the data loaded because it can be the same information as before; i need to find a way to make sure the user doesnt load the same file as 2h ago for example.
I thought about uploading the file with a different name each time and issuing an alter table command to change the name of the file in the definition of the external table, but it sounds kinda risky.
I also thought about marking each row in the file with a sequence to help differentiate files, but i doubt the client would accept it as they would need to manually do this (the file is exported from somewhere).
Is there any better way to make sure i don't load the same file in the external table except changing the file's name and executing an alter on the table?
Thank you
when you bring the data from external table to your database you can use MERGE command instead of insert. it let you don't worry about duplicate data
see the blog about The Oracle Merge Command
What's more, we can wrap up the whole transformation process into this
one Oracle MERGE command, referencing the external table and the table
function in the one command as the source for the MERGED Oracle data.
alter session enable parallel dml;
merge /*+ parallel(contract_dim,10) append */
into contract_dim d
using TABLE(trx.go(
CURSOR(select /*+ parallel(contracts_file,10) full (contracts_file) */ *
from contracts_file ))) f
on d.contract_id = f.contract_id
when matched then
update set desc = f.desc,
init_val_loc_curr = f.init_val_loc_curr,
init_val_adj_amt = f.init_val_adj_amt
when not matched then
insert values ( f.contract_id,
f.desc,
f.init_val_loc_curr,
f.init_val_adj_amt);
So there we have it - our complex ETL function all contained within a
single Oracle MERGE statement. No separate SQL*Loader phase, no
staging tables, and all piped through and loaded in parallel
I can only think of a solution somewhat like this:
Have a timestamp encoded in the datafile name (like: YYYYMMDDHHMISS-file.csv), where YYYYMMDDHHMISS is the timestamp.
Create a table with the fields timestamp (as above).
Create a shell scripts that:
extracts the timestamp from the datafilename.
calls an sqlscript with the timestamp as the parameter, and return 0 if that timestamp does not exist, <>0 if the timestamp already exist, and in that case exit the script with the error: File: YYYYMMDDHHMISS-file.csv already loaded.
copy the YYYYMMDDDHHMISS-file.csv to input-file.csv.
run the sql loader script that loads the input-file.csv file
when succes: run a second sql script with parameter timestamp that inserts the record in the database to indicate that the file is loaded and move the original file to a backup folder.
when failure: report the failure of the load script.
I have a dozen web servers each writing data to a log file. At the beginning of each hour, the data from the previous hour is loaded to hive using a cron script running the command:
hive -e "LOAD DATA LOCAL INPATH 'myfile.log' INTO TABLE my_table PARTITION(dt='2015-08-17-05')"
In some cases, the command fails and exits with a code other than 0, in which case our script awaits and tries again. The problem is, in some cases of failure, the data loading does not fail, even though it shows a failure message. How can I know for sure whether or not the data has been loaded?
Example for such a "failure" where the data is loaded:
Loading data to table default.my_table partition (dt=2015-08-17-05)
Failed with exception
org.apache.hadoop.hive.ql.metadata.HiveException: Unable to alter
partition. FAILED: Execution Error, return code 1 from
org.apache.hadoop.hive.ql.exec.MoveTask
Edit:
Alternatively, is there a way to query hive for the filenames loaded into it? I can use DESCRIBE to see the number of files. Can I know their names?
About "which files have been loaded in a partition":
if you had used an EXTERNAL TABLE and just uploaded your raw data
file in the HDFS directory mapped to LOCATION, then you could
(a) just run a hdfs dfs -ls on that directory from command line (or use the equivalent Java API call)
(b) run a Hive query such as select distinct INPUT__FILE__NAME from (...)
but in your case, you copy the data into a "managed" table, so there
is no way to retrieve the data lineage (i.e. which log file was used
to create each managed datafile)
...unless you add explicitly the original file name inside the log file, of
course (either on "special" header record, or at the beginning of each record - which can be done with good old sed)
About "how to automagically avoid duplication on INSERT": there is a way, but it would require quite a bit of re-engineering, and would cost you in terms of processing time /(extra Map step plus MapJoin)/...
map your log file to an EXTERNAL TABLE so that you can run an
INSERT-SELECT query
upload the original file name into your managed table using INPUT__FILE__NAME pseudo-column as source
add a WHERE NOT EXISTS clause w/ correlated sub-query, so that if the source file name is already present in target then you load nothing more
INSERT INTO TABLE Target
SELECT ColA, ColB, ColC, INPUT__FILE__NAME AS SrcFileName
FROM Source src
WHERE NOT EXISTS
(SELECT DISTINCT 1
FROM Target trg
WHERE trg.SrcFileName =src.INPUT__FILE__NAME
)
Note the silly DISTINCT that is actually required to avoid blowing away the RAM in your Mappers; it would be useless with a mature DBMS like Oracle, but the Hive optimizer is still rather crude...
I don't believe you can simply do this is in Hadoop/Hive. So here are the basics of an implementation in python:
import subprocess
x=subprocess.check_output([hive -e "select count(*) from my_table where dt='2015-08-17-05'"])
print type(x)
print x
But you have to spend some time working with backslashes to get hive -e to work using python. It can be very difficult. It may be easier to write a file with that simple query in it first, and then use hive -f filename. Then, print the output of subprocess.check_output in order to see how the output is stored. You may need to do some regex or type conversions, but I think it should just come back as a string. Then simply use an if statement:
if x > 0:
pass
else:
hive -e "LOAD DATA LOCAL INPATH 'myfile.log' INTO TABLE my_table PARTITION(dt='2015-08-17-05')"
I have a requirement to insert bulk data into an Oracle database from a CSV file. Now table columns specs match those of the CSV file's header with the exception of three additional fields in database:
A Primary Key field (for which a simple SEQUENCE.NEXTVAL is called)
A field for the name of the CSV file
A field for the last modified date+time of the file
The following stack question address an extra column issue, but the solution is pretty easy because it used Oracle sysdate which is internally available. I need to pass a parameter from either batch script/shell script.
Insert actual date time in a row with SQL*loader
Can PARFILE help here somehow?
My other alternative would be to do the whole task in two steps by writing a small java code:
Use SQL Loader for bulk upload leaving out data for the filename and
modified time
And then run a separate update statement to populate the newly
created rows
But I'm looking for something which will get the job done in one shot. Any advice??
I'm affraid it's not possible with sqlldr alone.
There is no tools for this in sqlldr.
You'd need some sort of script or a program to dynamically create a .ctl file for each load.
Here is a bash script to help you get started:
#!/bin/bash -xv
readonly MY_FILENAME=$1
readonly DB_BUF_TABLE=$2
readonly SQLLDR_CTL="LOAD DATA
CHARACTERSET UTF8
APPEND INTO TABLE $DB_BUF_TABLE
FIELDS TERMINATED BY ';'(
filename \"$MY_FILE_NAME\",
col_foo,
col_bar
)"
echo "$SQLLDR_CTL" > "loader.ctl"
sqlldr control=loader.ctl parfile=loader.par data="$MY_FILENAME"
sqlldrReturnValue=$?
You'd needsome locking with this.. or path separation for concurrent loads to be sure sqlldr starts with proper ctl file
I've tried a few different google searches but can't find any best practices or tutorials that address this.
This is the first time I've used a VS database project. I've imported an existing database (everything looks fine) and now I want to populate some of the tables post-deployment.
There is a Script.PostDeployment.sql file that includes the following header:
/*
Post-Deployment Script Template
--------------------------------------------------------------------------------------
This file contains SQL statements that will be appended to the build script.
Use SQLCMD syntax to include a file in the post-deployment script.
Example: :r .\myfile.sql
Use SQLCMD syntax to reference a variable in the post-deployment script.
Example: :setvar TableName MyTable
SELECT * FROM [$(TableName)]
--------------------------------------------------------------------------------------
*/
I'm wondering if from the last three lines there is some expected way to write these scripts using variables instead of just pure T-SQL syntax?
Should I be writing
INSERT INTO [dbo].[BlackAdder] VALUES ('edmund')
INSERT INTO [dbo].[BlackAdder] VALUES ('baldrick')
or
setvar [dbo].[BlackAdder] BlackAdder
INSERT INTO [$(BlackAdder)] VALUES ('edmund')
INSERT INTO [$(BlackAdder)] VALUES ('baldrick')
Does the latter allow some sort of compile-time check so that if setvar cannot resolve [dbo].[BlackAdder] that the project will give me some error?
If you open the project Properties folder, and click on Database.sqlcmvars you will see 3 vars already defined $(DefaultDataPath), $(DtabaseName) and $(DefaultLogPath) and can define your own here.
The setvar would be the other way around:
:setvar BlackAdder [dbo].[BlackAdder]
but ideally you define these in Database.sqlcmvars.
The intended use is for deploying your database project into multiple environments by defining SQLCMD variables and including them in your pre-deployment and post-deployment scripts.
How to: Define Variables for Database Projects
Property Files in Database and Server Projects