I'd like to switch an actual system importing data into a PostgreSQL 9.5 database from CSV files to a more efficient system.
I'd like to use the COPY statement because of its good performance. The problem is that I need to have one field populated that is not in the CSV file.
Is there a way to have the COPY statement add a static field to all the rows inserted ?
The perfect solution would have looked like that :
COPY data(field1, field2, field3='Account-005')
FROM '/tmp/Account-005.csv'
WITH DELIMITER ',' CSV HEADER;
Do you know a way to have that field populated in every row ?
My server is running node.js so I'm open to any cost-efficient solution to complete the files using node before COPYing it.
Use a temp table to import into. This allows you to:
add/remove/update columns
add extra literal data
delete or ignore records (such as duplicates)
, before inserting the new records into the actual table.
-- target table
CREATE TABLE data
( id SERIAL PRIMARY KEY
, batch_name varchar NOT NULL
, remote_key varchar NOT NULL
, payload varchar
, UNIQUE (batch_name, remote_key)
-- or::
-- , UNIQUE (remote_key)
);
-- temp table
CREATE TEMP TABLE temp_data
( remote_key varchar -- PRIMARY KEY
, payload varchar
);
COPY temp_data(remote_key,payload)
FROM '/tmp/Account-005'
;
-- The actual insert
-- (you could also filter out or handle duplicates here)
INSERT INTO data(batch_name, remote_key, payload)
SELECT 'Account-005', t.remote_key, t.payload
FROM temp_data t
;
BTW It is possible to automate the above: put it into a function (or maybe a prepared statement), using the filename/literal as argument.
Set a default for the column:
alter table data
alter column field3 set default 'Account-005'
Do not mention it the the copy command:
COPY data(field1, field2) FROM...
Related
For Eg:
1)File has
ID|Name|job|hobby|salary|hobby2
2)Data:
1|ram|architect|tennis|20000|cricket
1|ram|architect|football|20000|gardening
2|krish|teacher|painting|25000|cooking
3)Table:
Columns in table: ID-Name-Job-Hobby-Salary
Is it possible to load data into table as below:
1-ram-architect-tenniscricketfootbalgardening-20000
2-krish-teacher-paintingcooking-25000
Command: db2 "Load CLIENT FROM ABC.FILE of DEL MODIFIED BY coldel0x7x keepblanks REPLACE INTO tablename(ID,Name,Job,Hobby,salary) nonrecoverable"
You cannot achieve what you think you want in a single action with either LOAD CLIENT or IMPORT.
You are asking to denormalize, and I presume you understand the consequences.
Regardless, you can use a multi-step approach, first load/import into a temporary table, and then in a second step use SQL to denormalize into the final table, before discarding the temporary table.
Or if you are adept with awk , and the data file is correctly sorted, then you can pre-process the file externally to a database before load/import.
Or use an ETL tool.
You may use the INGEST command instead of LOAD.
You must create the corresponding infrastructure for this command beforehand with the following command, for example:
CALL SYSINSTALLOBJECTS('INGEST', 'C', 'USERSPACE1', NULL);
Load your file afterwards with the following command:
INGEST FROM FILE ABC.FILE
FORMAT DELIMITED by '|'
(
$id INTEGER EXTERNAL
, $name CHAR(8)
, $job CHAR(20)
, $hobby CHAR(20)
, $salary INTEGER EXTERNAL
, $hobby2 CHAR(20)
)
MERGE INTO tablename
ON ID = $id
WHEN MATCHED THEN
UPDATE SET hobby = hobby CONCAT $hobby CONCAT $hobby2
WHEN NOT MATCHED THEN
INSERT (ID, NAME, JOB, HOBBY, SALARY) VALUES($id, $name, $job, $hobby CONCAT $hobby2, $salary);
I'm creating new table then inserting values in it because the tsv file doesn't have headers so i need to create table structure first then insert the value. I'm trying to insert the value in database table which is been created. I'm using df.to_sql function to insert tsv values into database table but its creating table but it's not inserting values in that table and its not giving any type of error either.
I have tried to create new table through sqalchemy and insert value it worked but it didn't worked for already created table.
conn, cur = create_conn()
engine = create_engine('postgresql://postgres:Shubham#123#localhost:5432/walmart')
create_query = '''create table if not exists new_table(
"item_id" TEXT, "product_id" TEXT, "abstract_product_id" TEXT,
"product_name" TEXT, "product_type" TEXT, "ironbank_category" TEXT,
"primary_shelf" TEXT, apparel_category" TEXT, "brand" TEXT)'''
cur.execute(create_query)
conn.commit()
file_name = 'new_table'
new_file = "C:\\Users\\shubham.shinde\\Desktop\\wallll\\new_file.txt"
data = pd.read_csv(new_file, delimiter="\t", chunksize=500000, error_bad_lines=False, quoting=csv.QUOTE_NONE, dtype="unicode", iterator=True)
with open(file_name + '_bad_rows.txt', 'w') as f1:
sys.stderr = f1
for df in data:
df.to_sql('new_table', engine, if_exists='append')
data.close()
I want to insert values from df.to_sql() into database table
Not 100% certain if this argument works with postgresql, but I had a similar issue when doing it on mssql. .to_sql() already creates the table in the first argument of the method in new_table. The if_exists = append also doesn't check for duplicate values. If data in new_file is overwritten, or run through your function again, it will just add to the table. As to why you're seeing the table name, but not seeing the data in it, might be due to the size of the df. Try setting fast_executemany=True as the second argument of the create_engine.
My suggestion, get rid of create_query, and handle the data types after to_sql(). Once the SQL table is created, you can use your actual SQL table, and join against this staging table for duplicate testing. The non-duplicates can be written to the actual table, converting datatypes on UPDATE to match the tables data type structure.
I am building an API server which accepts file uploads using multer.
I need to store an array of all the paths to all files uploaded for each request to a column in the PostgreSQL database which I have connected to the server.
Say I have a table created with the following query
CREATE TABLE IF NOT EXISTS records
(
id SERIAL PRIMARY KEY,
created_on TIMESTAMPTZ NOT NULL DEFAULT NOW(),
created_by INTEGER,
title VARCHAR NOT NULL,
type VARCHAR NOT NULL
)
How do I define a new column filepaths on the above table where I can insert a javascript string array (ex: ['path-to-file-1', 'path-to-file-2', 'path-to-file-3']).
Also how do I retrive, update/edit the list in javascript using node-postgres
You have 2 options:
use json or jsonb type. In the case string to insert will look:
'["path-to-file-1", "path-to-file-2", "path-to-file-3"]'
I would prefer jsonb - it allows to have good indexes. Json is rather just text with some additional built-in functions.
Use array of text - something like filepaths text[]. To insert you can use:
ARRAY ['path-to-file-1', 'path-to-file-2', 'path-to-file-3']
or
'{path-to-file-1,path-to-file-2,path-to-file-3,"path to file 4"}'
You need to use " here only for elements that contain space and so on. But you fill free to use it for all elements too.
You can create a file table that has a path column and a foreign key reference to the record that it belongs to. This way you can store the path as just a text column instead of storing an array in a column, which is better practice for relational databases. You'll also be able to store additional information on a file if you need to later. And it'll be more simple to interact with the file path records since you'd add a new file path by just inserting a new row into the file table (with the appropriate foreign key) and remove by deleting a row from the file table.
For example:
CREATE TABLE IF NOT EXISTS file (
record_id integer NOT NULL REFERENCES records(id) ON DELETE CASCADE,
path text NOT NULL
);
Then to get all the files for a record you can join the two tables together and convert to an array if you want.
For example:
SELECT
records.*,
ARRAY (
SELECT
file.path
FROM
file
WHERE
records.id = file.record_id
) AS file_paths
FROM
records;
Sample input (using only the title field of records):
INSERT INTO records (title) VALUES ('A'), ('B'), ('C');
INSERT INTO file (record_id, path) VALUES (1, 'patha1'), (1, 'patha2'), (1, 'patha3'), (2, 'pathb1');
Sample output:
id | title | file_paths
----+-------+------------------------
1 | A | {patha1,patha2,patha3}
2 | B | {pathb1}
3 | C | {}
I am currently working on a Cassandra 3 database in which one of its tables has a column that is defined like this:
column_name map<int, frozen <set<int>>>
When I have to change the value of a complete set given a map key x I just have to do this:
UPDATE keyspace.table SET column_name[x] = {1,2,3,4,5} WHERE ...
The thing is that I need to insert a value on a set given a key. I tried with this:
UPDATE keyspace.table SET column_name[x] = column_name[x] + {1} WHERE ...
But it returns:
SyntaxException: line 1:41 no viable alternative at input '[' (... SET column_name[x] = [column_name][...)
What am I doing wrong? Does anyone know how to insert data the way I need?
Since the value of map is frozen, you can't use update like this.
A frozen value serializes multiple components into a single value. Non-frozen types allow updates to individual fields. Cassandra treats the value of a frozen type as a blob. The entire value must be overwritten.
You have to read the full map get the value of the key append new item and then reinsert
[Question from customer]
I have following data in a text file. Delimited by |
A | null , ZZ
C | D
When I run this query using HDInsight:
CREATE EXTERNAL TABLE myfiledata(
col1 string,
col2 string
)
row format delimited fields terminated by '|' STORED AS TEXTFILE LOCATION 'wasb://.....';
I get the following result as expected:
A null , ZZ
C D
But when I run the same query using SQL DW Polybase, it throws error:
Query aborted-- the maximum reject threshold (0 rows) was reached while reading from an external source: 1 rows rejected out of total 1 rows processed.
How do I fix this?
Here's my script in SQL DW:
-- Creating external data source (Azure Blob Storage)
CREATE EXTERNAL DATA SOURCE azure_storage1
WITH
(
TYPE = HADOOP
, LOCATION ='wasbs://....blob.core.windows.net'
, CREDENTIAL = ASBSecret
)
;
-- Creating external file format (delimited text file)
CREATE EXTERNAL FILE FORMAT text_file_format
WITH
(
FORMAT_TYPE = DELIMITEDTEXT
, FORMAT_OPTIONS (
FIELD_TERMINATOR ='|'
, USE_TYPE_DEFAULT = TRUE
)
)
;
-- Creating external table pointing to file stored in Azure Storage
CREATE EXTERNAL TABLE [Myfile]
(
Col1 varchar(5),
Col2 varchar(5)
)
WITH
(
LOCATION = '/myfile.txt'
, DATA_SOURCE = azure_storage1
, FILE_FORMAT = text_file_format
)
;
We’re currently working on a way to bubble up the reason for reject to the user.
In the meantime, here's what's happening:
The default # of rows allowed to fail schema matching is 0. This means that if at least one of the rows you’re loading in from /myfile.txt doesn’t match the schema. In Hive, strings can accommodate an arbitrary amount of chars, but varchars cannot. In this case it’s failing on the varchar(5) for “null , ZZ” because that is more than 5 characters.
If you’d like to change the REJECT_VALUE in the CREATE EXTERNAL TABLE call, that will let through the other row – more info can be found here: https://msdn.microsoft.com/library/dn935021(v=sql.130).aspx
It's due to dirty record for the respective file format, for example in the case of parquet if the column contains '' (empty string) then it won't work, and will throw Query aborted-- the maximum reject threshold
[AZURE.NOTE] A query on an external table can fail with the error "Query aborted-- the maximum reject threshold was reached while reading from an external source". This indicates that your external data contains dirty records. A data record is considered 'dirty' if the actual data types/number of columns do not match the column definitions of the external table or if the data doesn't conform to the specified external file format. To fix this, ensure that your external table and external file format definitions are correct and your external data conform to these definitions. In case a subset of external data records is dirty, you can choose to reject these records for your queries by using the reject options in CREATE EXTERNAL TABLE DDL.