My actual data in csv extracts starts from line 10. How can I skip top few lines in snowflake load using copy or any other utility. Do we have anything similar to SKIP_HEADER ?
I have files on S3 and its my stage. I would be creating a snowpipe later on this datasource.
yes there is a skip_header option for CSV, allowing you to skip a specified number of rows, when defining a file format. Please have a look here:
https://docs.snowflake.net/manuals/sql-reference/sql/create-file-format.html#type-csv
So you create a file format associated with the csv files you have in mind and then use this when calling the copy commands.
Related
Is there an option to load a CSV into Redshift while skipping over a footer?
Just like we use ignoreheader when we want to ignore initial rows. If we want to ignore last rows is there any way?
No. There is no parameter to tell the COPY command to ignore rows at the end of a file.
However, you could load the file with an error by specifying a MAXERROR of 1, which will allow the file to load with one bad row (or more, if required).
I have job in Redshift that is responsible for pulling 6 files every month from S3. File names follow a standard naming convention as "file_label_MonthNameYYYY_Batch01.CSV". I'd like to modify the below COPY command to change the file naming in the S3 directory dynamically so I won't have to hard code the Month Name and YYYY and batch number. Batch number ranges 1-6.
Currently, here is what I have which is not efficient:
COPY tbl_name ( column_name1, column_name2, column_name3 )
FROM 'S3://bucket_name/folder_name/Static_File_Label_July2021_Batch01.CSV'
CREDENTIALS 'aws_access_key_id = xxx;aws_secret_access_key = xxxxx'
removequotes
EMPTYASNULL
BLANKSASNULL
DATEFORMAT 'MM/DD/YYYY'
delimiter ','
IGNOREHEADER 1;
COPY tbl_name ( column_name1, column_name2, column_name3 )
FROM 'S3://bucket_name/folder_name/Static_File_Label_July2021_Batch02.CSV'
CREDENTIALS 'aws_access_key_id = xxx;aws_secret_access_key = xxxxx'
removequotes
EMPTYASNULL
BLANKSASNULL
DATEFORMAT 'MM/DD/YYYY'
delimiter ','
IGNOREHEADER 1;
The dynamic file name shall change to August2021_Batch01 & August2021_Batch02 next month and so forth. Is there a way to do this? Thank you in advance.
There are lots of approaches to this. Which one is best for your case will depend on your circumstances. You need a layer in your process that controls configuring SQL for each month. Here are some ways to consider:
Use a manifest file - This file will have the S3 object names to
load. Your processing / file prep can update this file
Use a fixed load folder where the files are located for COPY, then
move these files to perm storage location after COPY.
Use variables in you bench to set the Month value and replace this
in when the SQL is issued to Redshift.
Write some code (Lambda?) to issue the SQL you are looking for
Last I checked you could leave the object name incomplete and all
matching objects would be loaded. Leave off the batch number and
suffix and load all the files with one text change.
It is desirable to load multiple files with a COPY command (uses more nodes in parallel) and options 1, 2, and 5 do this.
When specifying the FROM location of files to load, you can specify a partial filename.
Here is an example from COPY examples - Amazon Redshift:
The following example loads the SALES table with tab-delimited data from lzop-compressed files in an Amazon EMR cluster. COPY loads every file in the myoutput/ folder that begins with part-.
copy sales
from 'emr://j-SAMPLE2B500FC/myoutput/part-*'
iam_role 'arn:aws:iam::0123456789012:role/MyRedshiftRole'
delimiter '\t' lzop;
Therefore, you could specify:
FROM 'S3://bucket_name/folder_name/Static_File_Label_July2021_*'
You would just need to change the Month & Year identifier. All files with that prefix would be loaded in one batch.
I want to create a CSV file which contains the results of query.
This CSV file will live in Google Cloud Storage. (This query is around 15GB) I need it to be a single file. Is it possible, if so how?
CREATE OR REPLACE TABLE `your-project.your-dataset.chicago_taxitrips_mod` AS (
WITH
taxitrips AS (
SELECT
trip_start_timestamp,
trip_end_timestamp,
trip_seconds,
trip_miles,
pickup_census_tract,
dropoff_census_tract,
pickup_community_area,
dropoff_community_area,
fare,
tolls,
extras,
trip_total,
payment_type,
company,
pickup_longitude,
pickup_latitude,
dropoff_longitude,
dropoff_latitude,
IF((tips/fare >= 0.2),
1,
0) AS tip_bin
FROM
`bigquery-public-data.chicago_taxi_trips.taxi_trips`
WHERE
trip_miles > 0
AND fare > 0)
SELECT
trip_start_timestamp,
trip_end_timestamp,
trip_seconds,
trip_miles,
pickup_census_tract,
dropoff_census_tract,
pickup_community_area,
dropoff_community_area,
fare,
tolls,
extras,
trip_total,
payment_type,
company,
tip_bin,
ST_AsText(ST_SnapToGrid(ST_GeogPoint(pickup_longitude,
pickup_latitude), 0.1)) AS pickup_grid,
ST_AsText(ST_SnapToGrid(ST_GeogPoint(dropoff_longitude,
dropoff_latitude), 0.1)) AS dropoff_grid,
ST_Distance(ST_GeogPoint(pickup_longitude,
pickup_latitude),
ST_GeogPoint(dropoff_longitude,
dropoff_latitude)) AS euclidean,
CONCAT(ST_AsText(ST_SnapToGrid(ST_GeogPoint(pickup_longitude,
pickup_latitude), 0.1)), ST_AsText(ST_SnapToGrid(ST_GeogPoint(dropoff_longitude,
dropoff_latitude), 0.1))) AS loc_cross
FROM
taxitrips
LIMIT
100000000
)
If BigQuery needs to output multiple files, you can then concatenate them into a single one with a gsutil operation for files in GCS:
gsutil compose gs://bucket/obj1 [gs://bucket/obj2 ...] gs://bucket/composite
https://cloud.google.com/storage/docs/gsutil/commands/compose
Note that there is a limit (currently 32) to the number of components that can be composed in a single operation.
Exporting 15GB to a single CSV file is not possible (to multiple files is possible). I tried your same query (Bytes processed 15.66 GB) then tried to export it to a CSV file in GCS but failed with this error
Table gs://[my_bucket]/bq_export/test.csv too large to be exported to a single file. Specify a uri including a * to shard export. See 'Exporting data into one or more files' in https://cloud.google.com/bigquery/docs/exporting-data.
BQ Documentation only allows you to export up to 1 GB of table data to a single file. Since the table exceeds 1GB then you have to use a wildcard like:
gs://your-bucket-name/csvfilename*.csv
Not sure why would you like the export csv file to be in a single file but IMHO it's too large to be in a single file. writing it to multiple files will be a lot faster since BQ would use its parallelism to write the output using multiple threads.
Is there any way/option or workaround to skip the entire file which contains bad entries , while loading the data from S3 to Redshift.
Please note that I am not talking about skipping the entries that are invalid in the file, but the entire file which contains bad entry or record.
By default Redshift fails entire file if you don't supply Maxerror option in Copy command. Its default behavior.
copy catdemo from 's3://awssampledbuswest2/tickit/category_pipe.txt' iam_role 'arn:aws:iam::<aws-account-id>:role/<role-name>' region 'us-west-2';
Above command will fail entire file and will not load any data from given file. Read the documentation here for more information.
If you specify, Maxerror option then only it ignores records upto that # from particular file.
copy catdemo from 's3://awssampledbuswest2/tickit/category_pipe.txt' iam_role 'arn:aws:iam::<aws-account-id>:role/<role-name>' region 'us-west-2' MAXERROR 500;
In above example Redshift will tolerate up-to 500 bad records.
I hope this answers your question, but If it doesn't please update the question and I will refocus the answer.
I have multiple small parquet files generated as output of hive ql job, i would like to merge the output files to single parquet file?
what is the best way to do it using some hdfs or linux commands?
we used to merge the text files using cat command, but will this work for parquet as well?
Can we do it using HiveQL itself when writing output files like how we do it using repartition or coalesc method in spark?
According to this https://issues.apache.org/jira/browse/PARQUET-460
Now you can download the source code and compile parquet-tools which is built in merge command.
java -jar ./target/parquet-tools-1.8.2-SNAPSHOT.jar merge /input_directory/
/output_idr/file_name
Or using a tool like https://github.com/stripe/herringbone
You can also do it using HiveQL itself, if your execution engine is mapreduce.
You can set a flag for your query, which causes hive to merge small files at the end of your job:
SET hive.merge.mapredfiles=true;
or
SET hive.merge.mapfiles=true;
if your job is a map-only job.
This will cause the hive job to automatically merge many small parquet files into fewer big files. You can control the number of output files with by adjusting hive.merge.size.per.task setting. If you want to have just one file, make sure you set it to a value which is always larger than the size of your output. Also, make sure to adjust hive.merge.smallfiles.avgsize accordingly. Set it to a very low value if you want to make sure that hive always merges files. You can read more about this settings in hive documentation.
Using duckdb :
import duckdb
duckdb.execute("""
COPY (SELECT * FROM '*.parquet') TO 'merge.parquet' (FORMAT 'parquet');
""")