# Step 3: Create data generator functionality

The following are several functions used to generate data. The utility function, `marketcap_to_DECIMAL`, is used by the `seed_trades` stored procedure to convert a string value for the market capitalization of a stock into a decimal value.

```sql
DELIMITER //
CREATE OR REPLACE FUNCTION marketcap_to_DECIMAL(s VARCHAR(15))
 RETURNS DECIMAL(18,2) AS
DECLARE
 m CHAR(1) = SUBSTR(s, LENGTH(s), 1); -- M or B
 raw_v DECIMAL(18,2) = SUBSTR(s, 2, LENGTH(s) - 1);
 v DECIMAL(18,2) = NULL;
BEGIN
 IF m = "B" THEN
   v = raw_v * 1000;
 ELSE
   v = raw_v;
 END IF;
 RETURN v;
END //
DELIMITER ;

```

The `seed_trades` stored procedure generates rows of “seed” trade data based on an integer input value. This provides a query to rank the companies by market capitalization limited to the top 200.

The stored procedure generates approximately the same number of trades for each company.

```sql
DELIMITER //
CREATE OR REPLACE PROCEDURE seed_trades(num_trades INT) RETURNS INT AS
DECLARE
 ranked_companies ARRAY(RECORD(Symbol VARCHAR(50), _rank INT));
DECLARE
 q QUERY(Symbol VARCHAR(50), _rank INT) =
   SELECT Symbol, rank() OVER (ORDER BY marketcap_to_DECIMAL(MarketCap)) AS _rank
   FROM company
   WHERE LENGTH(Symbol) < 5
   ORDER BY _rank DESC LIMIT 200;
 i INT = 0;
 rank_num INT;
 next_id INT = 1;
 sym CHAR(5);
 price_base DECIMAL(18,4);
 current_prices ARRAY(INT);
 l ARRAY(RECORD(Symbol VARCHAR(50), _rank INT));
BEGIN
 l = collect(q);
 FOR r IN l LOOP
   i += 1;
   rank_num = r._rank;
   sym = r.Symbol;
   price_base = FLOOR(rand() * 50) + 50;
   FOR j IN 1..((rank_num / 10) + RAND() * 10) LOOP
     INSERT trade VALUES(
       next_id,
       sym,
       FLOOR(1 + RAND() * 10) * 100, -- shares
       price_base,      -- share_price
       DATE_ADD(NOW(), INTERVAL RAND() * 6 HOUR)); -- random time during trading day, roughly
     next_id += 1;
     IF next_id > num_trades THEN RETURN(next_id); END IF;
   END LOOP;
 END LOOP;
 RETURN(next_id);
END //
DELIMITER ;

```

This last stored procedure, `iter_stocks`, generates additional trade events using a “random walk” to determine the next price for each company. It will store the current price for each company, then adds a random number between -1 and 1 to set the new price for each iteration.

Each iteration inserts new records equal to `num_shares`. When `iter_stocks` completes, the total number of records in the `trade` table will be equal to `num_shares` \* `iterations` + `num_shares`.

```sql
DELIMITER //
CREATE OR REPLACE PROCEDURE iter_stocks(iterations INT) as
DECLARE
   tickers ARRAY(CHAR(5));
   prices ARRAY(DECIMAL(18,4));
   last_ids ARRAY(bigINT);
   counts ARRAY(INT);
   next_id bigINT = 1;
   ticker CHAR(5);
   price DECIMAL(18,4);
   c INT;
   rand DECIMAL(18,4);
   tickers_q QUERY(t CHAR(5), p DECIMAL(18,4), lid BIGINT, c INT) = SELECT stock_symbol, share_price, MIN(id), COUNT(*) FROM trade GROUP BY stock_symbol;
   q ARRAY(RECORD(t CHAR(5), p DECIMAL(18,4), lid bigINT, c INT));
   q_count QUERY(c INT) = SELECT COUNT(*) FROM trade;
   total_c INT;
BEGIN
   q = COLLECT(tickers_q);
   tickers = CREATE_ARRAY(LENGTH(q));
   prices = CREATE_ARRAY(LENGTH(q));
   last_ids = CREATE_ARRAY(LENGTH(q));
   counts = CREATE_ARRAY(LENGTH(q));
   total_c = SCALAR(q_count);
   FOR r IN 0..LENGTH(q)-1 LOOP
       tickers[r] = q[r].t;
       prices[r] = q[r].p;
       last_ids[r] = q[r].lid;
       counts[r] = q[r].c;
   END LOOP;
   FOR j IN 0..(iterations-1) LOOP
       FOR i IN 0..LENGTH(tickers)-1 LOOP
           ticker = tickers[i];
           price = prices[i];
           next_id = last_ids[i];
           c = counts[i];
           rand = POW(-1, FLOOR(RAND()*2)) * RAND();
           INSERT INTO trade
           SELECT id + total_c, stock_symbol, shares, share_price + rand, trade_time FROM trade WHERE stock_symbol = ticker AND id >= next_id;
           prices[i] = price + rand;
           last_ids[i] = next_id + total_c;
       END LOOP;
   END LOOP;
END //
DELIMITER ;

```

***

Modified at: November 20, 2024

Source: [/cloud/query-data/advanced-query-topics/example-building-a-sample-stock-trade-database/step-3-create-data-generator-functionality/](https://docs.singlestore.com/cloud/query-data/advanced-query-topics/example-building-a-sample-stock-trade-database/step-3-create-data-generator-functionality/)

(An index of the documentation is available at /llms.txt)