Read MySQL result set with multiple columns and spaces - mysql

Pretend I have a MySQL table test that looks like:
+----+---------------------+
| id | value |
+----+---------------------+
| 1 | Hello World |
| 2 | Foo Bar |
| 3 | Goodbye Cruel World |
+----+---------------------+
And I execute the query SELECT id, value FROM test.
How would I assign each column to a variable in Bash using read?
read -a truncates everything after the first space in value:
mysql -D "jimmy" -NBe "SELECT id, value FROM test" | while read -a row;
do
id="${row[0]}"
value="${row[1]}"
echo "$id : $value"
done;
and output looks like:
1 : Hello
2 : Foo
3 : Goodbye
but I need it to look like:
1 : Hello World
2 : Foo Bar
3 : Goodbye Cruel World
I'm aware there are args I could pass to MySQL to format the results in table format, but I need to parse each value in each row. This is just a simplified example of my problem.

Use individual fields in the read loop instead of the array:
mysql -D "jimmy" -NBe "SELECT id, value FROM test" | while read -r id value;
do
echo "$id : $value"
done
This will make sure that id will be read into the id field and everything else would be read into the value field - that's how read behaves when input has more fields than the number of variables being read into. If there are more columns to be read, using a delimiter (such as #) that doesn't clash with actual data would help:
mysql -D "jimmy" -NBe "SELECT CONCAT(id, '#', value, '#', column3) FROM test" | while IFS='#' read -r id value column3;
do
echo "$id : $value : $column3"
done

You can do this, also avoid piping a command to a while read loop if possible to avoid creating a subshell.
while read -r line; do
id=$(echo $line | awk '{print $1}')
value=$(echo $line | awk '{print $1=""; print $0}'|sed ':a;N;$!ba;s/\n/ /g'| sed 's/^[ \t]*//g')
echo "ID: $id"
echo "VALUE: $value"
done< <(mysql -D "jimmy" -NBe "SELECT id, value FROM test")
If you want to store all the id's and values in an array for later use, you can modify it to look like this.
#!/bin/bash
declare -A -g arr
while read -r line; do
id=$(echo $line | awk '{print $1}')
value=$(echo $line | awk '{print $1=""; print $0}'|sed ':a;N;$!ba;s/\n/ /g'| sed 's/^[ \t]*//g')
arr[$id]=$value
done< <(mysql -D "jimmy" -NBe "SELECT id, value FROM test")
for key in "${!arr[#]}"; do
echo "$key: ${arr[$key]}"
done
Which gives you this output
dumbledore#ansible1a [OPS]:~/tmp/tmp > bash test.sh
1: Hello World
2: Foo Bar
3: Goodbye Cruel World

Related

Bash script with jq wont get date difference from strings, and runs quite slowly on i7 16GB RAM

Need to find the difference between TradeCloseTime and TradeOpenTime time in dd:hh:mm format for the Exposure column in the following script.
Also the script runs super slow (~4 mins for 800 rows of json, on Core i7 16gb RAM machine)
#!/bin/bash
echo "TradeNo, TradeOpenType, TradeCloseType, TradeOpenSource, TradeCloseSource, TradeOpenTime, TradeCloseTime, PNL, Exposure" > tradelist.csv
tradecount=$(jq -r '.performance.numberOfTrades|tonumber' D.json)
for ((i=0; i<$tradecount; i++))
do
tradeNo=$(jq -r '.trades['$i']|[.tradeNo][]|tonumber' D.json)
entrySide=$(jq -r '.trades['$i'].orders[0]|[.side][]' D.json)
exitSide=$(jq -r '.trades['$i'].orders[1]|[.side][]' D.json)
entrySource=$(jq -r '.trades['$i'].orders[0]|[.source][]' D.json)
exitSource=$(jq -r '.trades['$i'].orders[1]|[.source][]' D.json)
tradeEntryTime=$(jq -r '.trades['$i'].orders[0]|[.placedTime][]' D.json | tr -d 'Z' | tr -s 'T' ' ')
tradeExitTime=$(jq -r '.trades['$i'].orders[1]|[.placedTime][]' D.json | tr -d 'Z' | tr -s 'T' ' ')
profitPercentage=$(jq -r '(.trades['$i']|[.profitPercentage][0]|tonumber)*(100)' D.json)
echo $tradeNo","$entrySide","$exitSide","$entrySource","$exitSource","$tradeEntryTime","$tradeExitTime","$profitPercentage | tr -d '"' >> tradelist.csv
done
json file looks like this
{"market":{"exchange":"BINANCE_FUTURES","coinPair":"BTC_USDT"},"strategy":{"name":"","type":"BACKTEST","candleSize":15,"lookbackDays":6,"leverageLong":1.00000000,"leverageShort":1.00000000,"strategyName":"ABC","strategyVersion":35,"runNo":"002","source":"Personal"},"strategyParameters":[{"name":"DurationInput","value":"87.0"}],"openPositionStrategy":{"actionTime":"CANDLE_CLOSE","maxPerSignal":1.00000000},"closePositionStrategy":{"actionTime":"CANDLE_CLOSE","minProfit":"NaN","stopLossValue":0.07000000,"stopLossTrailing":true,"takeProfit":0.01290000,"takeProfitDeviation":"NaN"},"performance":{"startTime":"2019-01-01T00:00:00Z","endTime":"2021-11-24T00:00:00Z","startAllocation":1000.00000000,"endAllocation":3478.58904150,"absoluteProfit":2478.58904150,"profitPerc":2.47858904,"buyHoldRatio":0.62426630,"buyHoldReturn":4.57228387,"numberOfTrades":744,"profitableTrades":0.67833109,"maxDrawdown":-0.20924885,"avgMonthlyProfit":0.05242718,"profitableMonths":0.70370370,"avgWinMonth":0.09889897,"avgLoseMonth":-0.05275563,"startPrice":null,"endPrice":57623.08000000},"trades":[{"tradeNo":0,"profit":-5.48836165,"profitPercentage":-0.00549085,"accumulatedBalance":994.51163835,"compoundProfitPerc":-0.00548836,"orders":[{"side":"Long","placedTime":"2019-09-16T21:15:00Z","placedAmount":0.09700000,"filledTime":"2019-09-16T21:15:00Z","filledAmount":0.09700000,"filledPrice":10300.49000000,"commissionPaid":0.39965901,"source":"SIGNAL"},{"side":"CloseLong","placedTime":"2019-09-17T19:15:00Z","placedAmount":0.09700000,"filledTime":"2019-09-17T19:15:00Z","filledAmount":0.09700000,"filledPrice":10252.13000000,"commissionPaid":0.39778264,"source":"SIGNAL"}]},{"tradeNo":1,"profit":-3.52735800,"profitPercentage":-0.00356403,"accumulatedBalance":990.98428035,"compoundProfitPerc":-0.00901572,"orders":[{"side":"Long","placedTime":"2019-09-19T06:00:00Z","placedAmount":0.10000000,"filledTime":"2019-09-19T06:00:00Z","filledAmount":0.10000000,"filledPrice":9893.16000000,"commissionPaid":0.39572640,"source":"SIGNAL"},{"side":"CloseLong","placedTime":"2019-09-19T06:15:00Z","placedAmount":0.10000000,"filledTime":"2019-09-19T06:15:00Z","filledAmount":0.10000000,"filledPrice":9865.79000000,"commissionPaid":0.39463160,"source":"SIGNAL"}]},{"tradeNo":2,"profit":-5.04965308,"profitPercentage":-0.00511770,"accumulatedBalance":985.93462727,"compoundProfitPerc":-0.01406537,"orders":[{"side":"Long","placedTime":"2019-09-25T10:15:00Z","placedAmount":0.11700000,"filledTime":"2019-09-25T10:15:00Z","filledAmount":0.11700000,"filledPrice":8430.00000000,"commissionPaid":0.39452400,"source":"SIGNAL"},{"side":"CloseLong","placedTime":"2019-09-25T10:30:00Z","placedAmount":0.11700000,"filledTime":"2019-09-25T10:30:00Z","filledAmount":0.11700000,"filledPrice":8393.57000000,"commissionPaid":0.39281908,"source":"SIGNAL"}]}
You can do it all (extracts, conversions and formatting) with one jq call:
#!/bin/sh
echo 'TradeNo,TradeOpenType,TradeCloseType,TradeOpenSource,TradeCloseSource,TradeOpenTime,TradeCloseTime,PNL,Exposure'
query='
.trades[]
| [
.tradeNo,
.orders[0].side,
.orders[1].side,
.orders[0].source,
.orders[1].source,
(.orders[0].placedTime | fromdate | strftime("%Y-%m-%d %H:%M:%S")),
(.orders[1].placedTime | fromdate | strftime("%Y-%m-%d %H:%M:%S")),
.profitPercentage * 100,
(
(.orders[1].placedTime | fromdate) - (.orders[0].placedTime | fromdate)
| (. / 86400 | floor | tostring) + (. % 86400 | strftime(":%H:%M"))
)
]
|#csv
'
jq -r "$query" < D.json > tradelist.csv
example of JSON (cleaned of all irrelevant keys):
{
"trades": [
{
"tradeNo": 0,
"profitPercentage": -0.00549085,
"orders": [
{
"side": "Long",
"placedTime": "2018-12-16T21:34:46Z",
"source": "SIGNAL"
},
{
"side": "CloseLong",
"placedTime": "2019-09-17T19:15:00Z",
"source": "SIGNAL"
}
]
}
]
}
output:
TradeNo,TradeOpenType,TradeCloseType,TradeOpenSource,TradeCloseSource,TradeOpenTime,TradeCloseTime,PNL,Exposure
0,"Long","CloseLong","SIGNAL","SIGNAL","2018-12-16 21:34:46","2019-09-17 20:15:00",-0.549085,"274:22:40"
If you want to get rid of the double quotes that jq adds when generating a CSV (which are completely valid, but you need a real parser to read the CSV) then you can replace #csv with #tsv and post-process the output with tr '\t' ',', like this:
query='
...
|#tsv
'
jq -r "$query" < D.json | tr '\t' ',' > tradelist.csv
and you'll get:
TradeNo,TradeOpenType,TradeCloseType,TradeOpenSource,TradeCloseSource,TradeOpenTime,TradeCloseTime,PNL,Exposure
0,Long,CloseLong,SIGNAL,SIGNAL,2018-12-16 21:34:46,2019-09-17 20:15:00,-0.549085,274:22:40
note: This method of getting rid of the " in the CSV is only accurate when there is no \n \t \r \ , or " characters in the input data.
Regarding the main question (regarding computing time differences), you're in luck as jq provides the built-in function fromdateiso8601 for converting ISO times to "the
number of seconds since the Unix epoch (1970-01-01T00:00:00Z)".
With your JSON sample,
.trades[]
| [ .orders[1].placedTime, .orders[0].placedTime]
| map(fromdateiso8601)
| .[0] - .[1]
produces the three differences:
79200
900
900
And here's a function for converting seconds to "hh:mm:ss" format:
def hhmmss:
def l: tostring | if length < 2 then "0\(.)" else . end;
(. % 60) as $ss
| ((. / 60) | floor) as $mm
| (($mm / 60) | floor) as $hh
| ($mm % 60) as $mm
| [$hh, $mm, $ss] | map(l) | join(":");
I prefer using an intermediate structure of the "entry" and "exit" JSON. This helps with debugging the jq commands. Formatted for readability over performance:
#!/usr/bin/env bash
echo "TradeNo,TradeOpenType,TradeCloseType,TradeOpenSource,TradeCloseSource,TradeOpenTime,TradeCloseTime,PNL,Exposure" > tradelist.csv
jq -r '
.trades[]
|{tradeNo,
profitPercentage,
entry:.orders[0],
exit:.orders[1],
entryTS:.orders[0].placedTime|fromdate,
exitTS:.orders[1].placedTime|fromdate}
|[.tradeNo,
.entry.side,
.exit.side,
.entry.source,
.exit.source,
(.entry.placedTime|strptime("%Y-%m-%dT%H:%M:%SZ")|strftime("%Y-%m-%d %H:%M:%S")),
(.exit.placedTime|strptime("%Y-%m-%dT%H:%M:%SZ")|strftime("%Y-%m-%d %H:%M:%S")),
(.profitPercentage*100),
(.exitTS-.entryTS|todate|strptime("%Y-%m-%dT%H:%M:%SZ")|strftime("%d:%H:%M"))]|#csv
' D.json | tr -d '"' >> tradelist.csv
WARNING: This formatting assumes Exposure is LESS THAN 1 MONTH. Good luck with that!

JSON JQ filter by date older than bash

I have a json with this format of data in a text.json file
[
{
"name": "page/page1.html",
"properties": {
"lastModified": "2021-08-10T18:00:45+00:00",
}
},
{
"name": "page/page2.html",
"properties": {
"lastModified": "2021-08-10T19:24:23+00:00",
}
},
{
"name": "page/page3.html",
"properties": {
"lastModified": "2021-08-10T20:36:21+00:00",
}
}
]
I want to make a list of all the names of files which are last modified more that 30 minutes ago. This is my query at the moment to get a list of file names as a variable which i can use later.
file_names=`cat text.json | jq -r .[].name`
How can I use jq to filter for lastModified more than 30 minutes ago based on the timestamp in the properties so I only get the relevant file names?
I'd typically calculate the target date in native bash.
#!/usr/bin/env bash
# make sure we have bash new enough for printf %(...)T time-formatting
# this makes our script work even without GNU date
case $BASH_VERSION in
''|[123].*|4.[012].*) echo "ERROR: bash 4.3+ required" >&2; exit 1;;
esac
export TZ=UTC # force all timestamps to be in UTC (+00:00 / Z)
# faster, bash-builtin now=$(date +%s)
printf -v now '%(%s)T' -1
# faster, bash-builtin start_date_iso8601=$(date +%s -d '30 minutes ago')
start_date_epoch=$((now - 60*30))
printf -v start_date_iso8601 '%(%Y-%m-%dT%H:%M:%S+00:00)T' "$start_date_epoch"
# read our resulting names into an array (not a string)
# jq -j suppresses newlines so we can use NUL delimiters
while IFS= read -r -d '' name; do
names+=( "$name" )
done < <(
jq -j --arg start_date "$start_date_iso8601" '
.[] |
select(.properties.lastModified < $start_date) |
(.name, "\u0000")
' <text.json
)
# print the content of the array we just read the names into
printf 'Matching name: %q\n' "${names[#]}"
This seems to work
date=`date +%Y-%m-%d'T'%H:%M'Z' -d "15 min ago"`
file_names=`jq -r --arg date "$date" '.[] | select(.properties.lastModified < $date) | .name' < text.json`
Let jq do all date computations:
With bash 4 and above with mapfile:
mapfile -d '' last_modified < <(
jq --join-output '(now - 1800) as $date | .[] | select((.properties.lastModified | .[:18] + "Z" | fromdate) < $date) | .name + "\u0000"' input_file.json
)
# For debug purpose
declare -p last_modified
Without mapfile, records are delimited with ASCII RS control character rather than a null byte:
IFS=$'\36' read -ra last_modified < <(jq -j '(now - 1800) as $date | .[] | select((.properties.lastModified | .[:18] + "Z" | fromdate) < $date) | .name + "\u001e"' input_file.json)
Here is the stand-alone jq script with comments:
#!/usr/bin/env -S jq -jf
# Store current timestamp minus 30 minutes (1800 seconds) as $date
(now - 1800) as $date |
.[] |
#
select(
(
# Strip the numerical timezone offset out from the timestamp
# and replace it with the Z for UTC iso8601
# to make it an iso8601 date string that jq understands
.properties.lastModified | .[:18] + "Z" | fromdate
) < $date
) |
.name + "\u0000"

Dump Json response to a bash variable

I have the following ouput
[
"notimportant",
[
"val1",
"val2",
...,
"valn"
]
]
I'm trying to store every value into a bash string, using jq I tried this
out=''
req=$(curl -s $url)
len=$(echo $req | jq length )
for (( i = 0; i < $len; i++ )); do
element=$(echo $req | jq '.[1]' | jq --argjson i "$i" '.[$i]')
out=${element}\n${out}
done
which feels clunky and also has a slow performance. I'm trying to dump the values at once without looping on all the elements
With an array:
mapfile -t arr < <(curl -s "$url" | jq -r '.[1] | .[]')
declare -p arr
Do you want the values separate by TAB or NEWLINE characters in a single variable? The #tsv function is useful for controlling output:
outTABS=$(curl -s "$url" | jq -r '.[1]|.|#tsv')
outLINE=$(curl -s "$url" | jq -r '.[1]|.[]|[.]|#tsv')
> echo "$outTABS"
val1 val2 valn
> echo "$outLINE"
val1
val2
valn

jq create output in many separate files

given the following json:
[
{"_id":{"$oid":"6d2"},"jlo":"ΕΙ AJSB","dd":"d5f"},
{"_id":{"$oid":"c6d3"},"jlo":"ΕΙ ALKSB","dd":"5d9"},
{"_id":{"$oid":"b0cc6d4"},"jlo":"ΕΙ AGHTSB","dd":"1b1"},
{"_id":{"$oid":"6d2"},"jlo":"ΕPOWΙ AJSB","dd":"d5f"},
{"_id":{"$oid":"c6d3"},"jlo":"ΕGTΙ ALKSB","dd":"5d9"},
{"_id":{"$oid":"b0cc6d4"},"jlo":"ΕLKΙ AGHTSB","dd":"1b1"}
]
what i need to do is have as output for each discrete value of the ll element, the unique values of ta, in a separate file, named after a one to one representation where each dd code is substituted with a human readable representation:
d5f:departmentone
5d9:departmentalt
1b1:departshort
Desired output, in a per row basis, each unique value of jlo with the count of times it was found in each dd element so we get in the end something like this:
first file named departmentone.txt:
ΕΙ AJSB 1
ΕPOWΙ AJSB 1
second file named departmentalt.txt
ΕΙ ALKSB 1
ΕGTΙ ALKSB 1
third file named departshort.txt
ΕΙ AGHTSB 2
i have tried with map and reduce, group_by, sort_by, with really poor results
Only one invocation of jq is necessary. To allocate the output to the separate files, you can combine this one invocation with a single invocation to awk, or you could use a shell loop as illustrated below.
First, here's an illustration of how the shell pipeline would look:
jq -r --rawfile dd2name dd2name.tsv -f group.jq input.json |
while IFS=$'\t' read -r f v ; do echo "$v" >> "$f" ; done
This assumes that the mapping to filenames is in a TSV file named dd2name.tsv, and that the following jq program is in group.jq:
def dict:
split("\n") | map(select(length>0) | split("\t"))
| INDEX(.[0]) | map_values(.[1]);
($dd2name | dict) as $dict
| ($dict | keys_unsorted[]) as $dd
| map(select(.dd == $dd))
| group_by(.jlo)
| map("\($dict[$dd])\t\(.[0].jlo) \(length)")[]
As the name suggests, the dict function creates a dictionary giving the mapping of .dd values to the filenames. It assumes the availability of INDEX. If your jq does not have INDEX, then now would be an excellent time to upgrade your jq; otherwise, its def can easily be copied from builtin.jq (google: builtin.jq "def INDEX"), or you could replace the last line by: | reduce .[] as $p ({}; .[$p[0]] = $p[1]);
awk-based solution
The following invocation of awk can be used instead of the while ... done command above:
awk -F\\t 'fn && (fn!=$1) {close(fn)}; {fn=$1; print $2 >> fn}'
Season to taste
If the dd2name.tsv mapping file does not contain the ".txt" suffix, it can easily be added in any of a variety of ways, according to taste.
Note also that the proposed solutions above make some assumptions, notably that the .jlo values do not contain tabs, newlines, or NULs. If any of those assumptions is violated, then some tweaking will be required.
I'd do it in three passes, filtering the array with the desired dd and grouping by jlo, then extracting the jlo of the first (guaranteed) item of the array and its length :
map(select(.dd == "d5f")) | group_by(.jlo) | map("\(.[0].jlo) \(length)") | .[]
You can try it here.
Full bash run :
jq --arg dd d5f --raw-output 'map(select(.dd == $dd)) | group_by(.jlo) | map("\(.[0].jlo) \(length)") | .[]' yourJsonFile > departmentone.txt
jq --arg dd 5d9 --raw-output 'map(select(.dd == $dd)) | group_by(.jlo) | map("\(.[0].jlo) \(length)") | .[]' yourJsonFile > departmentalt.txt
jq --arg dd 1b1 --raw-output 'map(select(.dd == $dd)) | group_by(.jlo) | map("\(.[0].jlo) \(length)") | .[]' yourJsonFile > departmentshort.txt
Supposing you have a file named "mapping.txt" with the following content :
d5f:departmentone
5d9:departmentalt
1b1:departshort
You could extract those codes and labels to generate the files :
while IFS=: read -r code label; do
jq --arg dd $code --raw-output 'map(select(.dd == $dd)) | group_by(.jlo) | map("\(.[0].jlo) \(length)") | .[]' yourJsonFile > "$label".txt
done < mapping.txt

Get count based on value bash

I have data in this format in a file:
{"field1":249449,"field2":116895,"field3":1,"field4":"apple","field5":42,"field6":"2019-07-01T00:00:10","metadata":"","frontend":""}
{"field1":249448,"field2":116895,"field3":1,"field4":"apple","field5":42,"field6":"2019-07-01T00:00:10","metadata":"","frontend":""}
{"field1":249447,"field2":116895,"field3":1,"field4":"apple","field5":42,"field6":"2019-07-01T00:00:10","metadata":"","frontend":""}
{"field1":249443,"field2":116895,"field3":1,"field4":"apple","field5":42,"field6":"2019-07-01T00:00:10","metadata":"","frontend":""}
{"field1":249449,"field2":116895,"field3":1,"field4":"apple","field5":42,"field6":"2019-07-01T00:00:10","metadata":"","frontend":""}
Here, each entry represents a row. I want to have a count of the rows with respect to the value in field one, like:
249449 : 2
249448 : 1
249447 : 1
249443 : 1
How can I get that?
with awk
$ awk -F'[,:]' -v OFS=' : ' '{a[$2]++} END{for(k in a) print k, a[k]}' file
You can use the jq command line tool to interpret JSON data. uniq -c counts the number of occurences.
% jq .field1 < $INPUTFILE | sort | uniq -c
1 249443
1 249447
1 249448
2 249449
(tested with jq 1.5-1-a5b5cbe on linux xubuntu 18.04 with zsh)
Here's an efficient jq-only solution:
reduce inputs.field1 as $x ({}; .[$x|tostring] += 1)
| to_entries[]
| "\(.key) : \(.value)"
Invocation: jq -nrf program.jq input.json
(Note in particular the -n option.)
Of course if an object-representation of the counts is satisfactory, then
one could simply write:
jq -n 'reduce inputs.field1 as $x ({}; .[$x|tostring] += 1)' input.json
Using datamash and some shell utils, change the non-data delimiters to squeezed tabs, count field 3, (it'd be field 2, but there's a leading tab), reverse, then pretty print as per OP spec:
tr -s '{":,}' '\t' < file | datamash -sg 3 count 3 | tac | xargs printf '%s : %s\n'
Output:
249449 : 2
249448 : 1
249447 : 1
249443 : 1