Apache Airflow don ML Workflows
Apache Airflow dandamali ne mai buɗewa don yin rubutu, tsarawa, da sa ido kan ayyukan aiki azaman lamba.
Dubawa
In machine learning it acts as the conductor that triggers data pipelines, retraining jobs, and batch predictions on a reliable schedule.
Zurfafa nutsewa
An ƙirƙiri kwararar iska a Airbnb a cikin 2014 kuma yanzu aikin Apache ne. Ƙaƙwalwarta ta tsakiya ita ce DAG: Jagorar Acyclic Graph na ayyuka da aka ayyana a cikin Python, inda gefuna ke saita tsarin aiwatarwa da dogaro. Mai tsarawa yana nazarin waɗannan DAGs, ya yanke shawarar waɗanne ayyuka suke shirye, kuma ya aika da su ga masu zartarwa da ma'aikata; UI na gidan yanar gizo yana nuna tarihin gudu, rajistan ayyukan, da matsayin ɗawainiya. Ga ML, Airflow ana amfani dashi sosai azaman ƙungiyar makaɗa maimakon injin ƙididdigewa: baya horar da ƙirar kanta amma yana haifar da matakai kamar cire bayanai, inganta shi, ƙaddamar da aikin horo akan Spark ko Kubernetes pod, da tura sakamakon. Masu aiki da firikwensin suna barin ayyuka su kira tsarin waje, jira fayiloli, ko gudanar da kwantena. Ƙarfin sa shine abin dogaro da tsarin jadawalin, sake gwadawa, sake cikawa, da bayyananniyar gani cikin hadaddun bututun tushen lokaci.
Fahimtar Fasaha
Airflow DAG shine kawai lambar Python, don haka ana bayyana abubuwan dogaro ta hanyar shirye-shirye tare da masu aiki waɗanda aka ɗaure ta hanyar haɗin gwiwar bitshift ko APIs ɗawainiya. Mai tsara jadawalin yana ci gaba da kimanta kowane tazara na jadawalin DAG da abubuwan dogaro da aiki, yana yin layi kawai ayyuka waɗanda abin dogaronsu ya yi nasara. Masu zartarwa kamar Celery ko Kubernetes suna gudanar da waɗannan ayyuka akan ma'aikatan da aka rarraba. Ana bin kowane ɗawainiyar gudanar da aiki tare da jiha, rajistan ayyukan, da sake gwada dabaru, kuma ana adana metadata a cikin ma'ajin bayanai don cikakken tantancewa.
Dabarun Tasiri
Kudin da kasafin kuɗi
Hukunce-hukuncen gine-gine suna haifar da aiki da tsadar aiki na shekaru.
Shawarwari masu haske
Ilimin fasaha yana taimaka wa ƙungiyoyi su zaɓi tari mai kyau, ba kawai sabon abu ba.
Kula da inganci
Zaɓuɓɓukan injiniya mafi kyau suna rage abin dogaro a cikin samarwa.
Makomar Apache Airflow don ML Workflows
Airflow 2.x da 3.x suna jaddada mai tsara tsari mai sauri, API ɗin TaskFlow don tsabtace bututun Python, da kuma tsarin tsara bayanai inda DAGs ke haifar da sabuntawar saiti maimakon ƙayyadaddun agogo. Don ML, yi tsammanin haɗakarwa mai ƙarfi tare da shagunan sifofi da sake horon da abin ya faru. Ruwan iska yana ƙara sanya kansa a matsayin rukunin ƙungiyar kade-kade wanda ke daidaita kayan aiki na musamman kamar dbt, Spark, da Kubeflow, maimakon yin gasa da su, yana mai da matsayinsa na tsara kashin bayan bayanan zamani da ML.
Aiwatar da Gaskiyar Duniya
Kamfanin watsa labarai yana gudanar da DAG na Airflow na yau da kullun wanda ke jan rajistan ayyukan haɗin gwiwar mai amfani, sake horar da samfurin shawarwari, kuma yana sabunta cache ɗin sabis.
Ƙungiyar kasuwancin e-commerce tana amfani da na'urori masu auna firikwensin don jira fayil ɗin bayanan mai siyarwa zuwa ƙasa a cikin ma'ajiyar girgije kafin ƙaddamar da aikin hasashen ƙasa.
Wani kamfani na fintech yana tsara ayyukan sa'o'i na sa'o'i inda Airflow ke haifar da ƙirar kwantena don ƙaddamar da ma'amaloli masu tuhuma.
Ƙungiyoyin bayanai suna amfani da dawo da Airflow don sake sarrafa watanni na bayanan tarihi ta hanyar sabon bututun aikin injiniya bayan canji na hankali.
Hatsari & Tsare-tsare
Haɓaka ma'auni ɗaya na iya ɓoye manyan raunin tsarin.
Sau da yawa ana raina kayan more rayuwa da kuma kuɗin kulawa.
Tsaro da gibin lura na iya girma yayin da tsarin ke ƙara haɓaka.
Taswirar Hanya
Ƙayyade latency, inganci, da maƙasudin farashi kafin aiwatarwa.
Alamar ma'auni a ƙarƙashin ainihin kaya da yanayin bayanai.
Kula da kayan aiki don kurakurai, ɗigo, da tasirin mai amfani.
Shirya bijirowa da hanyoyin mayar da martani kafin sikeli.
Ci gaba da Bincike
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Jagora na gaba
Kubernetes don ML Workloads
Tambayoyin da ake yawan yi
What is Apache Airflow for ML Workflows?
Apache Airflow dandamali ne mai buɗewa don yin rubutu, tsarawa, da sa ido kan ayyukan aiki azaman lamba. A cikin koyan na'ura yana aiki a matsayin jagorar da ke haifar da bututun bayanai, sake horar da ayyuka, da tsinkayar tsari akan ingantaccen jadawalin.
A cikin Apache Airflow, menene ainihin abstraction da ake amfani dashi don ayyana tafiyar aiki?
An ayyana kwararar ayyukan iska a matsayin DAGs a cikin Python, inda ayyuka ke nodes kuma gefuna suna ayyana oda na kisa.
Wace rawa Airflow ya fi takawa a bututun ML?
Airflow mawaƙa ne: yana haifar da daidaita matakai kamar hakar bayanai da ayyukan horarwa maimakon yin ƙididdige nauyi da kanta.
Wanne ginin iska ne ake amfani da shi don jira yanayin waje, kamar fayil ɗin da ya isa wurin ajiya?
Na'urori masu auna firikwensin aiki ne na musamman waɗanda ke dakatar da tafiyar aiki har sai an cika sharadi, kamar saukowar fayil ko ɓangaren da ke bayyana.
Menene Airflow 'backfill' ke ba ku damar yi?
Ciki baya yana aiwatar da DAG a cikin tazarar da suka gabata, mai amfani don sake sarrafa tarihi bayan canjin dabarun bututun.
Wane bangare ne ke ci gaba da kimanta DAGs kuma ya yanke shawarar waɗanne ayyuka ne ke shirye don gudanar?
Mai tsara jadawalin yana nazarin DAGs, yana bincika tazara tsakanin jadawalin da abin dogaro, da kuma jerin ayyuka waɗanda matakan da ke sama suka yi nasara.