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SELECT 
    blocked_locks.pid AS blocked_pid,
    blocked_activity.usename AS blocked_user,
    blocking_locks.pid AS blocking_pid,
    blocking_activity.usename AS blocking_user,
    blocked_activity.query AS blocked_statement,
    blocking_activity.query AS current_statement_in_blocking_process,
    blocked_activity.application_name AS blocked_application,
    blocking_activity.application_name AS blocking_application
FROM pg_catalog.pg_locks blocked_locks

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DO $$
DECLARE r RECORD;
BEGIN
	FOR r IN <query that will return a record set for r to iterate over>
	LOOP 
		BEGIN  
			RAISE NOTICE 'Dealing with ID: %',r.id;
			UPDATE <table> as t1
			SET var1 = t2.var1 
			from <table2> t2

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DELETE FROM <table> a USING (
SELECT MIN(ctid) as ctid, var1, var2
  FROM <same_table> b
  GROUP BY 2,3 HAVING COUNT(*) > 1
) b
WHERE a.var1 = b.var1
and a.var2 = b.var2
AND a.ctid <> b.ctid

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--Create the materialized view
CREATE materialized view <schema_name>.mv_prompts AS
SELECT id, ngram, freq
FROM <schema_name>.prompts
WHERE add_conditions_here
ORDER BY freq DESC;

--Create a search index using GIN
CREATE INDEX prompts_ngram_idx 
ON <schema_name>.mv_prompts 

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import spacy
#Load the (small) model
_nlp = spacy.load('en_core_web_sm')

#Adjust the max length of the document
#_nlp.max_length = 1000000

#text contains the data that we want to extract phrases from, in string/buffer format

all_prompts = []

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import psycopg2
from collections import Counter

query_populate = """
	INSERT into <schema_name>.prompts (ngram, freq)
	values (%(ngram)s, %(freq)s) 
	ON CONFLICT (ngram) DO UPDATE
	SET freq = prompts.freq + %(freq)s
	WHERE prompts.ngram = %(ngram)s
	"""

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def prompts(cursor, search_string):
	'''
	In: cursor module, search_string a tsquery acceptable search string
	Out: Prompts dict
	'''
	
	default_data = {'prompts':[{'id' : 0, 'key': 'No prompts available'}]}
	prompts_data = {}
	
	query_get_prompts = """

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